This PDF file contains the front matter associated with SPIE Proceedings Volume 7258, including the Title Page, Copyright information, Table of Contents, In Memoriam: Robert F. Wagner, and the Conference Committee listing.

In order to discuss the cost-benefit ratio of CT examinations in children, one must be familiar with the reasons why CT can provide a high collective or individual dose. The reasons include increasing CT use as well as lack of attention to dose reduction strategies. While those have been substantial efforts for dose reduction, additional work is necessary to prevent unnecessary radiation exposure. This responsibility is shared between science and medicine, industry, regulatory agencies, and patients as well.

C-arm based cone-beam CT (CBCT) has evolved into a routine clinical imaging modality to provide threedimensional tomographic image guidance before, during, and after an interventional procedure. It is often used to update the clinician to the state of the patient anatomy and interventional tool placement. Due to the repeatedly use of CBCT, the accumulated radiation dose in an interventional procedure has become a concern. There is a strong desire from both patients and health care providers to reduce the radiation exposure required for these exams. The overall objective of this work is to propose and validate a method to significantly reduce the total radiation dose used during a CBCT image guided intervention. The basic concept is that the first cone-beam CT scan acquired at the full dose will be used to constrain the reconstruction of the later CBCT scans acquired at a much lower radiation dose. A recently developed new image reconstruction algorithm, Prior Image Constrained Compressed Sensing (PICCS), was used to reconstruct subsequent CBCT images with lower dose. This application differs from other applications of the PICCS algorithm, such as time-resolved CT or fourdimensional CBCT (4DCBCT), because the patient position may be frequently changed from one CBCT scan to another during the procedure. Thus, an image registration step to account for the change in patient position is indispensable for use of the PICCS image reconstruction algorithm. In this paper, the image registration step is combined with the PICCS algorithm to enable radiation dose reduction in CBCT image guided interventions. Experimental results acquired from a clinical C-arm system using a human cadaver were used to validate the PICCS algorithm based radiation dose reduction scheme. Using the proposed method in this paper, it has been demonstrated that, instead of 300 view angles, this technique requires about 20 cone-beam view angles to reconstruct CBCT angiograms. This signals a radiation dose reduction by a factor of approximately fifteen for subsequent acquisitions.

The purpose of this study is to develop a method for estimating patient-specific dose from abdomen-pelvis CT examinations and to investigate dose variation across patients in the same weight group. Our study consisted of seven pediatric patients in the same weight/protocol group, for whom full-body computer models were previously created based on the patients' CT data obtained for clinical indications. Organ and effective dose of these patients from an abdomen-pelvis scan protocol (LightSpeed VCT scanner, 120-kVp, 85-90 mA, 0.4-s gantry rotation period, 1.375-pitch, 40-mm beam collimation, and small body scan field-of-view) was calculated using a Monte Carlo program previously developed and validated for the same CT system. The seven patients had effective dose of 2.4-2.8 mSv, corresponding to normalized effective dose of 6.6-8.3 mSv/100mAs (coefficient of variation: 7.6%). Dose variations across the patients were small for large organs in the scan coverage (mean: 6.6%; range: 4.9%-9.2%), larger for small organs in the scan coverage (mean: 10.3%; range: 1.4%-15.6%), and the largest for organs partially or completely outside the scan coverage (mean: 14.8%; range: 5.7%-27.7%). Normalized effective dose correlated strongly with body weight (correlation coefficient: r = -0.94). Normalized dose to the kidney and the adrenal gland correlated strongly with mid-liver equivalent diameter (kidney: r = -0.97; adrenal glands: r = -0.98). Normalized dose to the small intestine correlated strongly with mid-intestine equivalent diameter (r = -0.97). These strong correlations suggest that patient-specific dose may be estimated for any other child in the same size group who undergoes the abdomen-pelvis scan.

Several experimental studies of the noise power spectrum (NPS) of cone-beam CT have been performed, but less attention has been paid to the analytical derivation of the 3D NPS. It is well known that noise in cone beam CT is nonstationary. When the image is reconstructed by using the FDK algorithm, different back-projection and cosine weightings are used for different reconstruction regions. In addition, the ray density and cone angle are also spatially dependent. As a result, a cone beam system has non-stationary noise. In order to characterize the noise behavior, we first construct the 3D NPS in a local reconstruction volume. Because cone beam rays passing through a small volume can be approximated as parallel rays, the 3D NPS of a small volume can be constructed by considering all effects. The 3D NPS of a large volume (which describes the average noise behavior but may not be valid throughout the volume) was generated by summing 3D NPS of small sub-volumes. The method was validated with computer simulations with uniform noise in the projection. 3D noise spectra of 3cm, 6cm, and 10 cm thick volumes were generated, and the radial NPS at different kz planes were compared with those of the analytically constructed 3D NPS. The results showed excellent matching for all cases. With the proposed method, non-stationary noise behavior of any local volume can be analyzed. The non-stationary noise behavior also causes a high-frequency roll-off in the NPS of a large volume, and as the volume size increases, the roll-off frequency decreases because the larger volume has more heterogeneous noise behavior.

Cone-beam systems designed for breast cancer detection bear a unique radiation dose limitation and are vulnerable to the additive noise from the detector. Additive noise is the signal fluctuation from detector elements and is independent of the incident exposure level. In this study, two different approaches (single pixel based and region of interest based) to measure the additive noise were explored using continuously acquired air images at different exposure levels, with both raw images and flat-field corrected images. The influence from two major factors, inter-pixel variance and image lag, were studied. The pixel variance measured from dark images was used as the gold standard (for the entire detector 15.12±1.3 ADU²) for comparison. Image noise propagation through reconstruction procedures was also investigated and a mathematically derived quadratic relationship between the image noise and the inverse of the radiation dose was confirmed with experiment data. The additive noise level was proved to affect the CT image noise as the second order coefficient and thus determines the lower limit of the scan radiation dose, above which the scanner operates at quantum limited region and utilizes the x-ray photon most efficiently.

We have previously introduced an intensity-weighted region-of-interest (IWROI) technique for image-guided radiation therapy (IGRT), where the outer ROI receives lower exposure than the inner ROI by use of intensity weighting (IW-) filters during the scan. Image noise level, as a result, in the outer ROI will be higher than that in the inner ROI after reconstruction. CBCT images are to be registered to planning CT images and there exist a number of imageregistration algorithms, some of which are relatively more robust against image noise. The IW-filters should be designed so that the outer ROI images have noise levels slightly less than the tolerance of the registiration algorithm resulting in maximum reduction to patient exposure. Therefore, a proper study can guide the filter design based on noise characteristics of the image reconstruction. As a part of the study, we investigated the noise propagation from the projections to the reconstructed image in this work. Also, we obtained the experimental noise characteristics of projections for varying exposure, simulated a pelvis imaging using the NCAT phantom, and performed an image registration of the reconstructed image to the phantom image.

We have investigated the relationship between scan parameters and image quality in fourdimensional cone-beam computed tomography (4D-CBCT) performed with a flat panel imager in image-guided radiotherapy. We have determined upper bounds on scan time while achieving objective thresholds of image quality, namely in noise performance and minimization of view aliasing artifacts. A slow-gantry design for 4D-CBCT was used, in which we slow down clinical linear accelerator gantry speed from the typical 1.0 rpm speed to 0.1 - 0.125 rpm, to ensure the projection angle spacing between two consecutive respiratory cycles is less than 3 degrees. A respiratory monitoring device was used to record the respiratory signal for temporal correlation of the projection data for 4D-CBCT image reconstruction. Four patient data sets were acquired. Reference images were reconstructed with all projection data and were compared with images reconstructed with 50%, 33% and 20% of the projection data. These three partial data reconstructions are simulations of scans with shorter acquisition times. The main image degradations in the short scan simulation image sets are streaking artifacts and poor signal to noise ratio, both caused by sparse projection sampling. The amount of streaking artifacts and SNR in each image set is quantified. By allowing some streaking artifacts and not compromising the assessment of tumor motion, we produce images that suggest that a reduction in scan time from 3 to 6 min to approximately 2 min may be possible, making 4D-CBCT feasible in a clinical setting.

The latest generation of nano computed tomography (nano-CT) systems with sub-micrometer focus X-ray source is expected to yield non-invasive imaging of internal microstructure of objects with isotropic spatial resolution in the range of hundreds nanometers. Most recently commercial systems have become available for purchase. The quantitative characterization of the performance of nano-CT systems is important for evaluating the accuracy of size and density measurements of fine details in nano-CT images. The point spread function (PSF) and modulation transfer function (MTF) are calculated most commonly from the measurement of thin wire phantom for measuring the spatial resolution of clinical CT systems. However, a consistent method for describing the spatial resolution of nano-CT has not been utilized due to the requirement of a nanowire which is a wire of diameter of the order of tens of nanometers. This paper presents a method to characterize the spatial resolution in x/y-scan plane (transversal orientation) of nano-CT systems using a relatively large microwire in the PSF measurement. In this method, the MTF computed from the PSF is estimated on the basis of a two-Gaussian PSF model. Experimenting with microwire images with three different diameter sizes (3μm, 10μm, 30μm) obtained by the synchrotron radiation CT, we demonstrate the potential usefulness of the method for describing the spatial resolutions of nano-CT systems.

Future generations of CT systems would need a mean to cover an entire organ in a single rotation. A way to accomplish this is to physically increase detector size to provide, e.g., 120~160mm z (head-foot) coverage at iso. The x-ray cone angle of such a system is usually 3~4 times of that of a 64-slice (40mm) system, which leads to more severe cone beam artifacts in cardiac scans. In addition, the extreme x-ray take-off angles for such a system cause severe heel effect, which would require an increase in anode target angle to compensate for it. One shortcoming of larger target angle is that tube output likely decreases because of shorter thermal length. This would result in an increase of image noise. Our goal is to understand from a physics and math point of view, what is the clinical acceptable level of artifacts, resolution, and noise impact. The image artifacts are assessed through computer simulation of a helical body phantom and visual comparison of reconstructed images between a 140mm system and a 64-slice system. The IQ impact from target angle increase is studied analytically and experimentally by first finding the proper range of target angles that give the acceptable heel effect, then estimating the impact on peak power (flux) and z resolution using an empirical model of heel effect for given target angle and analytical models of z resolution and tube current loading factor for given target thermal length. The results show that, for a 140mm system, 24.5% of imaging volume exhibits more severe cone beam artifacts than a 64-slice system, which also brings up a patient dose concern. In addition, this system may suffer from a 36% peak power (flux) loss, which is equivalent to about 20% image noise increase. Therefore, a wide coverage CT system using a single x-ray source is likely to face some severe challenges in IQ and clinical accuracy.

The tomographic reconstruction of the beating heart requires dedicated methods. One possibility is gated reconstruction, where only data corresponding to a certain motion state are incorporated. Another one is motioncompensated reconstruction with a pre-computed motion vector field, which requires a preceding estimation of the motion. Here, results of a new approach are presented: simultaneous reconstruction of a three-dimensional object and its motion over time, yielding a fully four-dimensional representation. The object motion is modeled by a time-dependent elastic transformation. The reconstruction is carried out with an iterative gradient-descent algorithm which simultaneously optimizes the three-dimensional image and the motion parameters. The method was tested on a simulated rotational X-ray acquisition of a dynamic coronary artery phantom, acquired on a C-arm system with a slowly rotating C-arm. Accurate reconstruction of both absorption coefficient and motion could be achieved. First results from experiments on clinical rotational X-ray coronary angiography data are shown. The resulting reconstructions enable the analysis of both static properties, such as vessel geometry and cross-sectional areas, and dynamic properties, like magnitude, speed, and synchrony of motion during the cardiac cycle.

Purpose: To achieve three dimensional isotropic dynamic cardiac CT imaging with high temporal resolution for evaluation of cardiac function with a slowly rotating C-arm system. Method and Materials: A recently introduced extension to compressed sensing, viz. Prior Image Constrained Compressed Sensing (PICCS), in which a prior image is used as a constraint in the reconstruction has enabled this application. An in-vivo animal experiment (e.g. a beagle model) was conducted using an interventional C-arm system. The imaging protocol was as follows: contrast was injected, the contrast equilibrated, breathing was suspended for ~14 seconds during which time 420 equally spaced projections were acquired. This data set was used to reconstruct a fully sampled blurred image volume using the conventional FDK algorithm (e.g. the prior image). Then the data set was retrospectively gated into 19 phases according to the recorded ECG signal (heart rate ~ 95bpm) and images were reconstructed with the PICCS algorithm. Results: Cardiac MR was used as the gold standard due to its high temporal resolution. The same short-axis slice was selected from the PICCS-CT data set and the MR data set. Manual contouring on the peak systolic and peak diastolic frames was performed to assess the ejection fraction contribution from this single plane. The calculated ejection fractions with PICCS-CT agreed well with the MR results. Conclusion: We have demonstrated the ability to use a slowly rotating interventional C-arm system in order to make measurements of cardiac function. The new technique provides high isotropic spatial resolution (~0.5 mm) along with high temporal resolution (~ 33 ms). The evaluation of cardiac function demonstrated a great agreement with single slice cardiac MR.

We present new acquisition modes of a recently introduced dual-source computed tomography (DSCT) system equipped with two X-ray tubes and two corresponding detectors, mounted onto the rotating gantry with an angular offset of typically 90°. Due to the simultaneous acquisition of complementary data, the minimum exposure time is reduced by a factor of two compared to a single-source CT system (SSCT). The correspondingly improved temporal resolution is beneficial for cardiac CT. Also, maximum table feed per rotation in a spiral mode can be increased by a factor of 2 compared to SSCT, which provides benefits both for cardiac CT and non-cardiac CT. In an ECG-triggered mode the entire cardiac volume can be scanned within a fraction of one cardiac RR-cycle. At a rotation time of 0.28s using a detector with 64×0.6 mm beam collimation, the scan time of the entire heart is less than 0.3s at a temporal resolution of 75 ms. It will be shown, that the extremely fast cardiac scan reduces the patient dose to a theoretical lowest limit: for a 120 kV scan the dose level for a typical cardiac CT scan is well below 2 mSv. Using further protocol optimization (scan range adaptation, 100kV), the radiation dose can be reduced below 1mSv.

This study evaluates new applications using a novel navigation system with electromagnetic (EM) tracking in clinical routine. The navigation system (iGuide CAPPA, CAS innovations, Erlangen, Germany) consists of a PC with dedicated navigation software, the AURORA tracking system (NDI, Waterloo Ontario, Canada) and needles equipped with small coils in their tips for EM navigation. After patient positioning a 3D C-arm data set of the spine region of interest is acquired. The images are reconstructed and the 3D data set is directly transferred to the navigation system. Image loading and image to patient registration are performed automatically by the navigation system. For image acquisition a C-arm system with DynaCT option (AXIOM Artis, Siemens Healthcare, Forchheim, Germany) was used. As new clinical applications we performed kyphoplasty for reconstruction of collapsed vertebrae. All interventions were carried out without any complication. After a single planning scan the radiologists were able to place the needle in the designated vertebra. During needle driving 2D imaging was performed just in a few cases for control reasons. The time between planning and final needle positioning was reduced in all cases compared to conventional methods. Moreover, the number of control scans could be markedly reduced. The deviation of the needle to the planned target was less than 2 mm. The use of DynaCT images in combination with electromagnetic tracking-based navigation systems allows a precise needle positioning for kyphoplasty.

C-arm systems may be used as front ends for cone-beam CT. The resulting image quality is affected by several factors, including the source trajectory, the reconstruction algorithm, and the accuracy of the data. The standard source trajectory is a circular arc spanning a little more than 180 degrees. However, since a planar source trajectory satisfies Tuy's completeness condition only within a subset of the source plane, the resulting images are bound to exhibit "cone-beam artifacts" off the source plane. The cure consists in using a source trajectory that satisfies Tuy's completeness condition everywhere within the volume of interest. Such a source trajectory must be non-planar. To keep the scan time short, the source trajectory should also consist of a single, smooth segment. A favorable source trajectory of this kind is a curve known as spherical spiral. We implemented a spherical spiral on a laboratory C-arm system, along with a standard circular arc. An anthropomorphic head phantom was scanned using both source trajectories and otherwise identical scan parameters. Images were reconstructed using a short scan version of the FDK algorithm (circular arc) and the cone-beam Fourierfiltered backprojection (CBFFBP) algorithm presented earlier. Images obtained with the circular arc showed cone-beam artifacts. Images obtained with the spherical spiral did not. The results also demonstrate the good performance of the CBFFBP algorithm.

Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect. Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast, projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual energy CT.

We create a series of detailed computerized phantoms to estimate patient organ and effective dose in pediatric CT and investigate techniques for efficiently creating patient-specific phantoms based on imaging data. The initial anatomy of each phantom was previously developed based on manual segmentation of pediatric CT data. Each phantom was extended to include a more detailed anatomy based on morphing an existing adult phantom in our laboratory to match the framework (based on segmentation) defined for the target pediatric model. By morphing a template anatomy to match the patient data in the LDDMM framework, it was possible to create a patient specific phantom with many anatomical structures, some not visible in the CT data. The adult models contain thousands of defined structures that were transformed to define them in each pediatric anatomy. The accuracy of this method, under different conditions, was tested using a known voxelized phantom as the target. Errors were measured in terms of a distance map between the predicted organ surfaces and the known ones. We also compared calculated dose measurements to see the effect of different magnitudes of errors in morphing. Despite some variations in organ geometry, dose measurements from morphing predictions were found to agree with those calculated from the voxelized phantom thus demonstrating the feasibility of our methods.

We perform simulation studies of proposed square and hexagonal geometries of a multi-source X-ray micro-computed tomography (CT) system. The system uses linear arrays of the carbon nano-tube (CNT)-based X-ray sources which are individually addressable. In the square geometry, two linear source arrays and two area detectors form a square; whereas in the hexagonal geometry, three linear source arrays and three area detectors form a hexagon. The tomographic angular sampling for both geometries requires no motion of the sources or subject. Based on the sinogram maps, the hexagonal geometry has improved angular coverage than the square geometry. The ordered-subset convex iterative algorithm is implemented in both geometries for reconstructions from cone-beam projection data. The reconstructed images from both geometries are generally consistent with the phantom, although some streaking artifacts due to the limited-angle nature of the geometries are observed. The two geometries show similar performance in resolution-noise tradeoff. The gap-free hexagonal geometry produces lower mean squared error in the reconstructed images; when gaps between the source arrays and detectors are introduced, the angular coverage of the hexagonal geometry degrades faster and becomes worse than the square geometry. The impact of gaps on the imaging properties must be studied further.

A number of groups are currently investigating tomographic imaging of the breast, but the optimal design and acquisition parameters for such systems remains uncertain. One useful tool for investigating optimal parameters is computer simulation software. A computer program that simulates xray transport through a breast object model followed by signal and noise propagation through a CsI flatpanel detector has been modified, restructured and enhanced in order to provide a fast yet sufficiently accurate research tool. The main focus of this work was to validate the simulated response of a CsI flatpanel detector with a real detector namely, the Paxscan 2520 (Varian Medical Systems, Salt Lake City, UT). Preliminary results indicate that the program provides comparable quantitative accuracy, that can be used to obtain accurate and meaningful results to assist in research in tomosynthesis and CT breast imaging system design.

Images of mastectomy breast specimens have been acquired with a bench top experimental Cone beam CT (CBCT) system. The resulting images have been segmented to model an uncompressed breast for simulation of various CBCT techniques. To further simulate conventional or tomosynthesis mammographic imaging for comparison with the CBCT technique, a deformation technique was developed to convert the CT data for an uncompressed breast to a compressed breast without altering the breast volume or regional breast density. With this technique, 3D breast deformation is separated into two 2D deformations in coronal and axial views. To preserve the total breast volume and regional tissue composition, each 2D deformation step was achieved by altering the square pixels into rectangular ones with the pixel areas unchanged and resampling with the original square pixels using bilinear interpolation. The compression was modeled by first stretching the breast in the superior-inferior direction in the coronal view. The image data were first deformed by distorting the voxels with a uniform distortion ratio. These deformed data were then deformed again using distortion ratios varying with the breast thickness and re-sampled. The deformation procedures were applied in the axial view to stretch the breast in the chest wall to nipple direction while shrinking it in the mediolateral to lateral direction re-sampled and converted into data for uniform cubic voxels. Threshold segmentation was applied to the final deformed image data to obtain the 3D compressed breast model. Our results show that the original segmented CBCT image data were successfully converted into those for a compressed breast with the same volume and regional density preserved. Using this compressed breast model, conventional and tomosynthesis mammograms were simulated for comparison with CBCT.

Breast density has been recognized as one of the major risk factors for breast cancer. However, breast density is currently estimated using mammograms which are intrinsically 2D in nature and cannot accurately represent the real breast anatomy. In this study, a novel technique for measuring breast density based on the segmentation of 3D cone beam CT (CBCT) images was developed and the results were compared to those obtained from 2D digital mammograms. 16 mastectomy breast specimens were imaged with a bench top flat-panel based CBCT system. The reconstructed 3D CT images were corrected for the cupping artifacts and then filtered to reduce the noise level, followed by using threshold-based segmentation to separate the dense tissue from the adipose tissue. For each breast specimen, volumes of the dense tissue structures and the entire breast were computed and used to calculate the volumetric breast density. BI-RADS categories were derived from the measured breast densities and compared with those estimated from conventional digital mammograms. The results show that in 10 of 16 cases the BI-RADS categories derived from the CBCT images were lower than those derived from the mammograms by one category. Thus, breasts considered as dense in mammographic examinations may not be considered as dense with the CBCT images. This result indicates that the relation between breast cancer risk and true (volumetric) breast density needs to be further investigated.

In this work, we investigated the visibility of microcalcifications in CCD-based cone beam CT (CBCT) breast imaging. A paraffin cylinder with a diameter of 135 mm and a thickness of 40 mm was used to simulate a 100% adipose breast. Calcium carbonate grains, ranging from 140-150 to 200-212 μm in size, were used to simulate the microcalcifications. Groups of 25 same size microcalcifications were arranged into 5 × 5 clusters. Each cluster was embedded at the center of a smaller (15 mm diameter) cylindrical paraffin phantom, which were inserted into a hole at the center of the breast phantom. The breast phantom with the simulated microcalcifications was scanned on a bench top experimental CCDbased cone beam CT system at various exposure levels with two CCD cameras: Hamamatsu's C4742-56-12ER and Dalsa 99-66-0000-00. 300 projection images were acquired over 360° and reconstructed with Feldkamp's backprojection algorithm using a ramp filter. The images were reviewed by 6 readers independently. The ratios of visible microcalcifications were recorded and averaged over all readers. These ratios were plotted as the function of measured image signal-to-noise ratio (SNR) for various scans. It was found that 94% visibility was achieved for 200-212 μm calcifications at an SNR of 48.2 while 50% visibility was achieved for 200-212, 180-200, 160-180, 150-160 and 140-150 μm calcifications at an SNR of 25.0, 35.3, 38.2, 42.2 and 64.4, respectively.

Digital breast tomosynthesis (DBT) shows potential for improving breast cancer detection. However, this technique has not yet been fully characterized with consideration of the various uncertainties in the imaging chain and optimized with respect to system acquisition parameters. To obtain maximum diagnostic information in DBT, system optimization needs to be performed across a range of patients and acquisition parameters to quantify their impact on tumor detection performance. In addition, a balance must be achieved between x-ray dose and image quality to minimize risk to the patient while maximizing the system's detection performance. To date, researchers have applied a task-based approach to the optimization of DBT with use of mathematical observers for tasks in the signal-known-exactly background-known-exactly (SKE/BKE) and signal-known-exactly background-known statistically (SKE/BKS) paradigms1-3. However, previous observer models provided insufficient treatment of the spatial correlations between multi-angle DBT projections, so we incorporated this correlation information into the modeling methodology. We developed a computational approach that includes three-dimensional variable background phantoms for incorporating background variability, accurate ray-tracing and Poisson distributions for generating noise-free and noisy projections of the phantoms, and a channelized-Hotelling observer4 (CHO) for estimating performance in DBT. We demonstrated our method for a DBT acquisition geometry and calculated the performance of the CHO with Laguerre-Gauss channels as a function of the angular span of the system. Preliminary results indicate that the implementation of a CHO model that incorporates correlations between multi-angle projections gives different performance predictions than a CHO model that ignores multi-angle correlations. With improvement of the observer design, we anticipate more accurate investigations into the impact of multi-angle correlations and background variability on the performance of DBT.

While diagnostic improvement via breast tomosynthesis has been notable, the full potential of tomosynthesis has not yet been realized. This is because of the complex task of optimizing multiple parameters that constitute image acquisition and thus affect tomosynthesis performance. Those parameters include dose, number of angular projections, and the total angular span of those projections. In this study, we investigated the effects of acquisition parameters, independent of each other, on the overall diagnostic image quality of tomosynthesis. Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of each specimen were acquired at 6.2 times typical single-view mammographic dose level. Images at lower dose levels were then simulated using a noise modification routine. Each projection image was supplemented with 84 simulated 3 mm 3D lesions embedded at the center of 84 non-overlapping ROIs. The projection images were then reconstructed using a filtered-back projection (FBP) algorithm at 224 different combinations of acquisition parameters to investigate which one of the many possible combinations maximized performance. Performance was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion detectability. Results showed that performance improved with an increase in the total acquisition dose level and the angular span. At a constant dose level and angular span, the performance rolled-off beyond a certain number of projections, indicating that simply increasing the number of projections in tomosynthesis may not necessarily improve its performance. The best performance was obtained with 15-17 projections spanning an angular arc of ~45° - the maximum tested in our study, and for an acquisition dose equal to single-view mammography. The optimization framework developed in this framework is applicable to other reconstruction techniques and other multi-projection systems.

Digital breast tomosynthesis (DBT) has been shown to decrease breast structural noise thus improving the detection of masses. However decreased detectability of microcalcifications was observed, and several studies have been performed to investigate the benefit of taking an additional central projection view after a DBT scan. Our study investigates the effect of variable angular dose distribution within a single DBT scan. Using a prototype DBT system with uniform angular dose distribution, several DBT scans (25 projection views over 40 degree angular range) were performed using different glandular doses. A subset of projection images was selected from each scan to form composite DBT scans (25 views each) with different angular dose distribution schemes (ADS). Two examples of ADS were: 1) seven central views with four times the dose of periphery; and 2) five central projections with six times the dose of periphery. The total dose for each ADS was the same as a reference scan with uniform dose distribution (1.5 mGy). They also had the same number of views and angular range, and were reconstructed using identical reconstruction filter settings. The detectability of calcifications, the 3D MTF and NPS of the system, and the ideal observer object detectability index for all cases were compared. The results showed that higher dose for the central views improve the detectability of calcifications. However magnitude of improvement depends on the reconstruction method and the size of the object.

Digital breast tomosynthesis (DBT) is a limited-view, limited-angle computed tomography (CT) technique that has the potential to yield improved lesion conspicuity over that of standard digital mammography. To maintain short acquisition time, the detector must have a rapid temporal response. Transient effects like lag and ghosting have been noted previously in digital mammography systems, but for the times between successive views (approx. 1 minute), their impact on image quality is generally negligible. However, tomosynthesis imaging requires much shorter times between projection images (< 1 s). Under these conditions, detectors that may have been acceptable for digital mammography may not be suitable for tomosynthesis. Transient effects will generally cause both a loss of signal and an increase in image noise. A cascaded systems analysis is used to determine the effect of lag on image quality in a DBT system. It is shown that in the projection images, lag results in artifacts appearing as a "trail" of prior exposures. The effect of lag on image quality is also evaluated with a simple Monte Carlo simulation of a cone-beam tomosynthesis image formation incorporating a filtered back-projection algorithm.

We previously proposed a three-dimensional computerized breast phantom that combines empirical data with the flexibility of mathematical models¹. The goal of this project is to enhance the breast phantom to include a more detailed anatomy than currently visible and create additional phantoms from different breast CT data. To improve the level of detail in our existing segmentations, the breast CT data is reconstructed at a higher resolution and additional image processing techniques are used to correct for noise and scatter in the image data. A refined segmentation algorithm is used that incorporates more detail than previously defined. To further enhance high-resolution detail, mathematical models, implementing branching algorithms to extend the glandular tissue throughout the breast and to define Cooper's ligaments, are under investigation. We perform the simulation of mammography and tomosynthesis using an analytical projection algorithm that can be applied directly to the mathematical model of the breast without voxelization². This method speeds up image acquisition, reduces voxelization artifacts, and produces higher resolution images than the previously used method. The realistic 3D computerized breast phantom will ultimately be incorporated into the 4DXCAT phantom^3-5 to be used for breast imaging research.

A major problem of high-resolution positron-emission-tomography (PET) are subject movements during acquisition. We propose a new motion compensation algorithm called "Blind Motion-Compensated Reconstruction" (BMCR) that is able to deal with frames of extremely low statistics in the case of smooth motion. Our algorithm reconstructs both image and rigid motion just from the recorded data and does not need any external motion tracking. This is achieved by combining image reconstruction and motion compensation into one mathematical framework which consists of a cost functional and an optimization method. The cost functional basically consists of a difference term which ensures consistency of the estimated parameters to the model and some regularization terms which render the problem mathematically well-posed. The optimization method aims at finding a pair of image and transformation/motion such that the cost functional is minimal. Such a combined framework can overcome problems of existing algorithms which separate reconstruction and motion compensation. These algorithms usually try to get the motion information by registering reconstructed frames one to each other (in image space). Their main drawback is that the registration step is likely to be of low accuracy or even fail completely for low-statistics frames. A quantitative and visual comparison suggests that BMCR is superior to state-of-the-art intrinsic methods.

Motion artifacts are a significant issue in medical image reconstruction. There are many methods for incorporating motion information into image reconstruction. However, there are fewer studies that focus on deformation regularization in motioncompensated image reconstruction. The usual choice for deformation regularization has been penalty functions based on the assumption that tissues are elastic. In the image registration field, there have been some methods proposed that impose deformation invertibility using constraints or regularization, assuming that organ motions are invertible transformations. However, most of these methods require very high memory or computation complexity, making them poorly suited for dealing with multiple images simultaneously in motion-compensated image reconstruction. Recently we proposed an image registration method that uses a simple penalty function based on a sufficient condition for the local invertibility of deformations.¹ That approach encourages local invertibility in a fast and memory-efficient way. This paper investigates the use of that regularization method for the more challenging problem of joint image reconstruction and nonrigid motion estimation. A 2D PET simulation (based on realistic motion from real patient CT data) demonstrates the benefits of such motion regularization for joint image reconstruction/registration.

Molecular imaging using dynamic positron emission tomography (PET) can provide in vivo images of physiologically or biochemically important parameters. Direct reconstruction of parametric images from dynamic PET sinograms is statistically more efficient than the conventional indirect methods, which perform image reconstruction and kinetic modeling in two separate steps. Most existing direct reconstruction methods are derived based on a known blood input function. This paper presents a direct reconstruction algorithm using a simplified reference tissue model, which does not require a blood input function. We have derived a minorization-maximization algorithm to find the penalized maximum likelihood solution. Computer simulations show that the proposed method has better bias-variance tradeoff than the conventional indirect method for estimating parametric images of receptor binding potential using dynamic PET.

Today, attenuation corrected SPECT, typically performed using CT or Gadolinium line source based transmission scans, is more and more becoming standard in many medical applications. Moreover, the information about the material density distribution provided by these scans is key for other artifact compensation approaches in advanced SPECT reconstruction. Major drawbacks of these approaches are the additional patient radiation and hardware/maintenance costs as well as the additional workflow effort, e.g. if the CT scans are not performed on a hybrid scanner. It has been investigated in the past, whether it is possible to recover this structural information solely from the SPECT scan data. However, the investigated methods often result in noticeable image artifacts due to cross-dependences between attenuation and activity distribution estimation. With the simultaneous reconstruction method presented in this paper, we aim to effectively prevent these typical cross-talk artifacts using a-priori known atlas information of a human body. At first, an initial 3D shape model is coarsely registered to the SPECT data using anatomical landmarks and each organ structure within the model is identified with its typical attenuation coefficient. During the iterative reconstruction based on a modified ML-EM scheme, the algorithm simultaneously adapts both, the local activity estimation and the 3D shape model in order to improve the overall consistency between measured and estimated sinogram data. By explicitly avoiding topology modifications resulting in a non-anatomical state, we ensure that the estimated attenuation map remains realistic. Several tests with simulated as well as real patient SPECT data were performed to test the proposed algorithm, which demonstrated reliable convergence behaviour in both cases. Comparing the achieved results with available reference data, an overall good agreement for both cold as well as hot activity regions could be observed (mean deviation: -5.98%).

Imaging in general is becoming increasingly important in the medical science. At the cell level it is possible to label and trace almost individual molecules in vivo to study biochemical reactions using microscopy. In vivo imaging of living organisms is today mainly accomplished by PET, SPECT and fMRI. The problem is that the spatial resolution for realistic image acquisition times is of the order 1-3 mm, which is a serious limitation. We propose a new imaging modality, based on the same principles as SPECT but with drastically improved efficiency and spatial resolution. This is achieved by incorporating a large number of x-ray lenses between the detectors and the object. In current SPECT a pin-hole geometry is standard, involving an unfortunate trade-off between efficiency and spatial resolution, our solution would change this. The agent for radiolabelling is assumed to be ¹²⁵I, with an emission peak at 27 keV, since it is widely used and easy to handle. The large area, photon counting detectors will consist of a columnar CsI scintillator coupled to a CMOS integrated circuit for electronic read-out. Our simulations of the entire system and of the detector indicate that a resolution of 50 μm for the system is possible.

The behaviour of spins at a classical level in the presence of an external magnetic field is completely described by the Bloch equation. This is the main equation governing the magnetic resonance imaging (MRI) system, and as such the Bloch equation is extensively used for design purposes. Here we have transferred the Bloch equation to the spherical coordinate system that, to the best of our knowledge, has not previously been applied in this field. The mathematical framework and the simulation results show that this fresh view of the Bloch equation provides better insight into the magnetic resonance (MR) phenomenon. In this mathematical framework, without using spinor space, the order of the Bloch equation is reduced in a much simpler way and can therefore provides a novel insight to the slice selection problem. Simulation results are presented for a variety of slice selective pulses, with and without post excitation rephasing gradients. In this paper nonlinear gradient is tried as well which shows an improvement in uniformity of the selected slice. It is feasible to find an analytic approximate solution to the Bloch equation in spherical coordinate system by adopting averaging techniques over spatial variables available available in nonlinear dynamical systems. We anticipate that our new description of the MR phenomenon will allow researchers to revisit the excitation pattern design question to achieve better slice selectivity or to find an optimal excitation pattern from a theoretical basis. This has the potential to result in practical improvements affecting all forms of MR imaging.

Parallel MRI can achieve increased spatiotemporal resolution in MRI by simultaneously sampling reduced k-space data with multiple receiver coils. One requirement that different parallel MRI techniques have in common is the need to determine spatial sensitivity information for the coil array. This is often done by smoothing the raw sensitivities obtained from low-resolution calibration images, for example via polynomial fitting. However, this sensitivity post-processing can be both time-consuming and error-prone. Another important factor in Parallel MRI is noise amplification in the reconstruction, which is due to non-unity transformations in the image reconstruction associated with spatially correlated coil sensitivity profiles. Generally, regularization approaches, such as Tikhonov and SVD-based methods, are applied to reduce SNR loss, at the price of introducing residual aliasing. In this work, we present a regularization approach using in vivo coil sensitivities in parallel MRI to overcome these potential errors into the reconstruction. The mathematical background of the proposed method is explained, and the technique is demonstrated with phantom images. The effectiveness of the proposed method is then illustrated clinically in a whole-heart 3D cardiac MR acquisition within a single breath-hold. The proposed method can not only overcome the sensitivity calibration problem, but also suppress a substantial portion of reconstruction-related noise without noticeable introduction of residual aliasing artifacts.

To understand the role of the tongue in speech production, it is desirable to directly image the motion and strain of the muscles within the tongue. Magnetic resonance tagging-which was originally developed for cardiac imaging-has previously been applied to image both two-dimensional and three-dimensional tongue motion during speech. However, to quantify three-dimensional motion and strain, multiple images yielding two-dimensional motion must be acquired at different orientations and then interpolated - a time-consuming task both in image acquisition and processing. Recently, a new MR imaging and image processing method called zHARP was developed to encode and track 3D motion from a single slice without increasing acquisition time. zHARP was originally developed and applied to cardiac imaging. The application of zHARP to the tongue is not straightforward because the tongue in repetitive speech does not move as consistently as the heart in its beating cycle. Therefore tongue images are more susceptible to motion artifacts. Moreover, these artifacts are greatly exaggerated as compared to conventional tagging because of the nature of zHARP acquisition. In this work, we re-implemented the zHARP imaging sequence and optimized it for the tongue motion analysis. We also optimized image acquisition by designing and developing a specialized MRI scanner triggering method and vocal repetition to better synchronize speech repetitions. Our method was validated using a moving phantom. Results of 3D motion tracking and strain analysis on the tongue experiments demonstrate the effectiveness of this method.

Neutron stimulated emission computed tomography (NSECT) is being developed as a non-invasive technique to diagnose iron overload in the liver. It uses inelastic scatter interactions between fast neutrons and iron nuclei to quantify localized distributions of iron within the liver. Preliminary studies have demonstrated the feasibility of iron overload detection through NSECT using a Monte-Carlo simulation model in GEANT4. The work described here uses the GEANT4 simulation model to analyze iron-overload detection sensitivity in NSECT. A simulation of a clinical NSECT system was designed in GEANT4. Simulated models were created for human liver phantoms with concentrations of iron varying from 0.5 mg/g to 20 mg/g (wet). Each liver phantom was scanned with 100 million neutron events to generate gamma spectra showing gamma-lines corresponding to iron in the liver. A background spectrum was obtained using a water phantom of equal mass as the liver phantom and was subtracted from each liver spectrum. The height of the gamma line at 847 keV (corresponding to ⁵⁶Fe) was used as a measure of the detected iron concentration in each background-corrected spectrum. The variation in detected gamma counts was analyzed and plotted as a function of the liver iron concentration to quantify measurement error. Analysis of the differences between the measured and expected value of iron concentration indicate that NSECT sensitivity for detection of iron in liver tissue may lie in the range of 0.5 mg/g - 1 mg/g, which represents a clinically significant range for iron overload detection in humans.

We describe an improved optoacoustic tomography method, that utilizes a diffusion-based photon propagation model in order to obtain quantified reconstruction of targets embedded deep in heterogeneous scattering and absorbing tissue. For the correction we utilize an iterative finite-element solution of the light diffusion equation to build a photon propagation model. We demonstrate image improvements achieved by this method by using tissue-mimicking phantom measurements. The particular strength of the method is its ability to achieve quantified reconstructions in non-uniform illumination configurations resembling whole-body small animal imaging scenarios.

Various medical imaging techniques exist to detect the early development of tissue damage. However, a widely commercialized device that can be easily used and is cost effective is still needed. Through a literature review, we examined ultrasound, microwave tomography, and ultra-wideband (UWB) technology. Out of these techniques, UWB is the most promising since it has the capability to detect small adjustments in dielectric properties, which can change with minor alterations in perfusion and internal pressure. These minor alterations are vital in detecting the onset of ischemia, which precedes many serious conditions affecting tissue health. In addition to its ability in detection, UWB also has the potential to become a widely accessible technology to hospitals. Using software called XFdtd, we simulated ultrawideband pulses propagating through planes designed to resemble tissue in its dielectric properties. After testing several sizes of the horn antenna and configurations for the wire and port, the antenna's near field was finally able to reach the distance necessary to penetrate the tissue model. The resulting graph of voltage versus time was generated from the received antenna signal and it will be compared to the graphs that result after the dielectric properties of the model have been changed to simulate tissue injury. Through this manipulation of the tissue model, the sensitivity and selectivity of UWB in measuring small fluctuations in perfusion can be determined. In this future work with XFdtd, we want to show that UWB is a novel and viable technique in detecting early tissue injury.

The near-ubiquity of large area, active matrix, flat-panel imagers (AMFPIs) in medical x-ray imaging applications is a testament to the usefulness and adaptability of the relatively simple concept of array pixels based on a single amorphous silicon (a-Si:H) TFT coupled to a pixel storage capacitor. Interestingly, the fundamental advantages of a-Si:H thin film electronics (including compatibility with very large area processing, high radiation damage resistance, and continued development driven by interest in mainstream consumer products) are shared by the rapidly advancing technology of polycrystalline silicon (poly-Si) TFTs. Moreover, the far higher mobilities of poly-Si TFTs, compared to those of a- Si:H, facilitate the creation of faster and more complex circuits than are possible with a-Si:H TFTs, leading to the possibility of new classes of large area, flat panel imagers. Given recent progress in the development of initial poly-Si imager prototypes, the creation of increasingly sophisticated active pixel arrays offering pixel-level amplification, variable gain, very high frame rates, and excellent signal-to-noise performance under all fluoroscopic and radiographic conditions (including very low exposures and high spatial frequencies), appears within reach. In addition, it is conceivable that the properties of poly-Si TFTs could allow the development of large area imagers providing single xray photon counting capabilities. In this article, the factors driving the possible realization of clinically practical active pixel and photon counting imagers based on poly-Si TFTs are described and simple calculational estimates related to photon counting imagers are presented. Finally, the prospect for future development of such imagers is discussed.

A dual mode current-programmed, current-output active pixel sensor (DCAPS) in amorphous silicon (a-Si:H) technology is introduced for digital X-ray imaging, and in particular, for hybrid fluoroscopic and radiographic imagers. Here, each pixel includes an extra capacitor that selectively is coupled to the pixel capacitance to realize the dual mode behavior. Pixel structure, operation and characteristics are presented. The proposed DCAPS circuit was fabricated and assembled using an in-house bottom gate inverted staggered a-Si:H thin film transistor (TFT) process. Gain, lifetime, transient performance as well as noise analysis were carried out. The results are promising and demonstrate that the DCAPS enables dual mode X-ray imaging while compensating for the long term electrical and thermal stress related a-Si TFT threshold voltage (V_t) shift.

Incomplete charge collection due to poor electron mobility in amorphous selenium (a-Se) results in depth-dependent signal variations. The slow signal rise-time for the portion of the induced charge due to electron-movement towards the anode and significant electron trapping cause ballistic deficit. In this paper, we investigate Frisch-grid detector design to reduce the depth dependent noise, increase the photon count-rate, and improve the spectral performance of positively biased amorphous selenium radiation detectors. In addition, we analyze the impact of using the Frisch grid detector design on x-ray sensitivity, detective quantum efficiency (DQE), modulation transfer function (MTF), and image lag of integrating-mode a-Se radiation detectors. Preliminary results based on theory are presented for emerging digital medical imaging modalities such as mammography tomosynthesis and fluoroscopy.

The SSXII is a novel x-ray imager designed to improve upon the performance limitations of conventional dynamic radiographic/fluoroscopic imagers related to resolution, charge-trapping, frame-rate, and instrumentation-noise. The SSXII consists of a CsI:Tl phosphor coupled via a fiber-optic taper (FOT) to an electron-multiplying CCD (EMCCD). To facilitate investigational studies, initial designs enable interchangeability of such imaging components. Measurements of various component and configuration characteristics enable an optimization analysis with respect to overall detector performance. Photon transfer was used to characterize the EMCCD performance including ADC sensitivity, read-noise, full-well capacity and quantum efficiency. X-ray sensitivity was measured using RQA x-ray spectra. Imaging components were analyzed in terms of their MTF and transmission efficiency. The EMCCD was measured to have a very low effective read-noise of less than 1 electron rms at modest EMCCD gains, which is more than two orders-ofmagnitude less than flat panel (FPD) and CMOS-based detectors. The variable signal amplification from 1 to 2000 times enables selectable sensitivities ranging from 8.5 (168) to over 15k (300k) electrons per incident x-ray photon with (without) a 4:1 FOT; these sensitivities could be readily increased with further component optimization. MTF and DQE measurements indicate the SSXII performance is comparable to current state-of-the-art detectors at low spatial frequencies and far exceeds them at higher spatial frequencies. The instrumentation noise equivalent exposure (INEE) was measured to be less than 0.3 μR out to 10 cycles/mm, which is substantially better than FPDs. Component analysis suggests that these improvements can be substantially increased with further detector optimization.

In addition to causing loss of contrast and blurring in an image, scatter also makes quantitative measurements of xray attenuation impossible. Many devices, methods, and models have been developed to eliminate, estimate, and correct for the effects of scatter. Although these techniques can reduce the impact of scatter in a large-area image, no methods have proven to be practical and sufficient to enable quantitative analysis of image data in a routine clinical setting. This paper describes a method of scatter correction which uses moderate x-ray collimation in combination with a correction algorithm operating on data obtained from large-area flat panel detector images. The method involves acquiring slot collimated images of the object, and utilizing information from outside of the collimated region, in addition to a priori data, to estimate the scatter within the collimated region. This method requires no increase dose to the patient while providing high image quality and accurate estimates of the primary x-ray data. This scatter correction technique was validated through beam stop experiments and comparison of theoretically calculated and measured contrast of thin aluminum and polymethylmethacrelate objects. Measurements taken with various background material thicknesses, both with and without a grid, showed that the slot-scatter corrected contrast and the theoretical contrast were not significantly different given a 99% confidence interval. However, the uncorrected contrast was found to be significantly different from the corrected and theoretical contrasts. These findings indicate that this method of scatter correction can eliminate the effect of scatter on contrast and potentially enable quantitative x-ray imaging.

For task specific evaluation of imaging systems it is necessary to obtain detailed descriptions of their noise and deterministic properties. In the past we have developed an experimental and theoretical methodology to estimate the deterministic detector response of a digital x-ray imaging system, also known as the H matrix. In this paper we have developed the experimental methodology for the evaluation of the quantum and electronic noise of digital radiographic detectors using the covariance matrix K. Using the H matrix we calculated the transfer of a simulated coronary artery constriction through an imaging system's detector, and with the covariance matrix we calculated the detectability (or Signal-to-Noise Ratio) and the detection probability. The eigenvalues and eigenvectors of the covariance matrix were presented and the electronic and quantum noise were analyzed. We found that the exposure at which the electronic noise equals the quantum noise at 90 kVp was 0.2 μR. We compared the ideal Hotelling observer with the Fourier definition of the SNR for a toroidal stenosis on a cylindrical vessel. Because of the shift-invariance and cyclo-stationarity assumptions, the Fourier SNR overestimates the performance of imaging systems. This methodology can be used for task specific evaluation and optimization of a digital x-ray imaging system.

In digital radiography, conventional DQE evaluations are performed under idealized conditions that do not reflect typical clinical operating conditions. For this reason, we have developed and evaluated an experimental methodology for measuring theeffective detective quantum efficiency (eDQE) of digital radiographic systems and its utility in chest imaging applications.To emulate the attenuation and scatter properties of the human thorax across a range of sizes, the study employed pediatric and adult geometric chest imaging phantoms designed for use in the FDA/CDRH Nationwide Evaluation of X-Ray Trends (NEXT) program and a third phantom configuration designed to represent the bariatric population. The MTF for each phantom configuration was measured using images of an opaque edge device placed at the nominal surface of each phantom and at a common reference point. For each phantom, the NNPS was measured in a uniform region within the phantom image acquired at an exposure level determined from a prior phototimed acquisition. Scatter measurements were made using a beam-stop technique. These quantities were used along with measures of phantom attenuation and estimates of x-ray flux, to compute the eDQE at the beam-entrance surface of the phantoms, reflecting the presence of scatter, grid, magnification, and focal spot blur. The MTF results showed notable degradation due to focal spot blurring enhanced by geometric magnification, with increasing phantom size. Measured scatter fractions were 33%, 34% and 46% for the pediatric, adult, and bariatric phantoms, respectively. Correspondingly, the measured narrow beam transmission fractions were 16%, 9%, and 3%. The eDQE results for the pediatric and adult phantoms correlate well at low spatial frequencies but show degradation in the eDQE at increasing spatial frequencies for the adult phantom in comparison to the pediatric phantom. The results for the bariatric configuration showed a marked decrease in eDQE in comparison to the adult phantom results, across all spatial frequencies, attributable to the combined differences in geometric magnification, and scatter. The eDQE metric has been demonstrated to be sensitive to body habitus suggesting its usefulness in assessing system response across a range of chest sizes and potentially making it a useful factor in protocol assessment and optimization.

In digital mammography noise characteristics are measured in quality control procedures. In the European Guidelines a method of measurement to investigate noise in digital mammography systems was proposed to evaluate the presence of additional noise beside quantum noise. However this method of noise analysis does not discriminate sufficiently between systems with and without additional noise. Therefore a different noise analysis is proposed. In this analysis the noise of a digital system is subdivided into three components: electronic, quantum and structured noise and the noise dose dependency of these components is studied. The usefulness of this analysis in both the frequency and spatial domain is investigated on a number of DR and CR systems. The results show that large differences between digital mammography systems exists. Some systems do have a large range in detector dose for which quantum noise is the largest noise component. For one system however, electronic and structured noise are more dominant. In addition to the differences between systems smaller differences in noise characteristics exist between different target-filter combinations on a particular system. These differences might be attributed to the limited flatfield calibration, the heel effect and difference in sensitivity. The noise analysis in both the frequency and spatial domain give useful information about the noise characteristics of systems. The analysis in the spatial domain is relatively easy to perform and to interpret. This analysis might be suitable for QC purposes. The analysis in the frequency domain does give additional information and might be used for thorough investigations.

European Guidelines for quality control in digital mammography specify minimum and achievable standards of image quality in terms of threshold contrast, based on readings of images of the CDMAM test object by human observers. However the methodology is time-consuming and has large inter- and intra-observer error. To overcome these problems a software program is available to automatically read CDMAM images. An alternative approach would be to predict threshold contrast from measurements of DQE and MTF using a model of the imaging process. A simple signal-matched noise-integration model has been used to predict the contrast detail response of five different types of commercial digital mammography system (Siemens Inspiration, GE Senographe DS, and three types of Konica Minolta computerised radiography system). Measurements were made of the MTF and DQE of each detector and the noise equivalent apertures calculated. For each system sets of 16 images of the CDMAM test object were acquired at a range of dose levels and contrast-detail plots obtained using human observers and automated reading. The theoretically and experimentally determined threshold contrasts were compared. An encouragingly good level of agreement was found between the experimental data and theoretical predictions.

A common method for evaluating projection mammography is Contrast-Detail (CD) curves derived from the CD phantom for Mammography (CDMAM). The CD curves are derived either by human observers, or by automated readings. Both methods have drawbacks which limit their reliability. The human based reading is significantly affected by reader variability, reduced precision and bias. On the other hand, the automated methods suffer from limited statistics. The purpose of this paper is to develop a simple and reliable methodology for the evaluation of mammographic imaging systems using the Signal Known Exactly/Background Known Exactly (SKE/BKE) detection task for signals relevant to mammography. In this paper, we used the spatial definition of the ideal, linear (Hotelling) observer to calculate the task-specific SNR for mammography and discussed the results. The noise covariance matrix as well as the detector response H matrix of the imaging system were estimated and used to calculate the SNR_SKEBKE for the simulated discs of the CDMAM. The SNR as a function of exposure, disc diameter and thickness were calculated.

Amorphous selenium (a-Se) has been incorporated successfully in direct conversion flat panel x-ray detectors, and has demonstrated superior image quality in screening mammography and digital breast tomosynthesis (DBT) under energy integration mode. The present work explores the potential of a-Se for photon counting detectors in DBT. We investigated major factors contributing to the variation in the charge collected by a pixel upon absorption of each x-ray photon. These factors included x-ray photon interaction, detector geometry, charge transport, and the pulse shaping and noise properties of the photon counting readout circuit. Experimental measurements were performed on a linear array test structure constructed by evaporating an a-Se layer onto an array of 100 μm pitch strip electrodes, which are connected to a 32 channel low noise photon counting integrated circuit. The measured pulse height spectrum (PHS) under polychromatic xray exposure was interpreted quantitatively using the factors identified. Based on the understanding of a-Se photon counting performance, design parameters were proposed for a 2D detector with high quantum efficiency and count rate that could meet the requirements of photon counting detector for DBT.

We detail the integration of amorphous silicon (a-Si) active pixel sensor (APS) test arrays with an overlying amorphous selenium (a-Se) x-ray photoconductor, and report on results of their x-ray response and imaging properties. The a-Se/a-Si APS arrays incorporate a two-transistor (2T) gate-switched pixel amplifier architecture designed to provide high detector array resolution, as well as a controllable on-pixel gain. The direct x-ray detectors consist of in-house fabricated, dual mode active and passive sensor arrays with detector element (del) pitches of 100 μm and 200 μm, coated with 80 μm thick stabilized amorphous selenium. These selenium layers were selected for preliminary work and represent a quantum efficiency (QE) of 69% for x-ray spectra (tungsten target, 2 mm Al filtration) of 30 kVp. Detector response was evaluated for a-Se biasing electric fields of both 5 V/μm and 10 V/μm. A detector dark current of 110 pA/cm² (0.01 pA/100 μm del) at 10V/μm electric field, a controllable detector conversion gain up to 15.3 nA/mR at 30 kVp were measured. Active pixel gains of 6.7 and 9.6 were measured for 100μm and 200μm pitch detectors respectively. The amplified readout exhibits a better detection limit (by one order of magnitude) compared to the passive readout implemented on the same pixel. Capabilities of amplified pixels such as nondestructive readout, as well as programmable pixel conversion gain, and dynamic range control are demonstrated. In light of their adaptable gain and dynamic range, these detectors represent a promising technology for high-resolution high gain x-ray digital imaging, particularly in mammography tomosynthesis.

A novel mammography detector with dual amorphous-Selenium (α-Se) layer has been developed that employs photoinduced discharge in its readout procedure. The detector consists of a bias electrode, a thick α-Se layer for x-ray-to-electron conversion, an electron-trapping layer (ETL), a thin α-Se layer for the photoinduced discharge, alternately arranged transparent and opaque stripe electrodes, and a linear optical source for readout. The detector directly converts x-rays into electrons to accumulate the electrons in ETL. When photoinduced discharge arises on the transparent electrodes through readout light irradiation, an accumulated electron image is transferred to the transparent electrodes and detected as signals at charge amplifiers, which we call 'Photoconductive Switching' readout. Readout efficiency and image readout speed have been improved enough to be used as a practical level by the adoption of the alternatelyarranged stripe electrodes. Furthermore, such a simple stripe-electrode structure accomplishes low electrical-noise readout and easy fabrication of fine-pitch pixels. A prototype 50 ìm pixel-pitch detector with the 18×24 cm imaging area has been prepared, which shows high DQE performances more than 64, 48, and 28% at 1, 4, and 7 lp/mm, respectively, not only in the usual dose range of around 100 μGy but at the low dose of 32 μGy. The 'Photoconductive Switching' readout mechanism makes it possible to realize the high DQE and the finest resolution of 50 μm in the direct-conversion detectors for full-field digital mammography.

We present the first evaluation of a recently developed silicon-strip detector for photon-counting dual-energy breast tomosynthesis. The detector is well suited for tomosynthesis with high dose efficiency and intrinsic scatter rejection. A method was developed for measuring the spatial resolution of a system based on the detector in terms of the three-dimensional modulation transfer function (MTF). The measurements agreed well with theoretical expectations, and it was seen that depth resolution was won at the cost of a slightly decreased lateral resolution. This may be a justifiable trade-off as clinical images acquired with the system indicate improved conspicuity of breast lesions. The photon-counting detector enables dual-energy subtraction imaging with electronic spectrumsplitting. This improved the detectability of iodine in phantom measurements, and the detector was found to be stable over typical clinical acquisition times. A model of the energy resolution showed that further improvements are within reach by optimization of the detector.

Recently, Tomosynthesis (TS) has been evaluated as a useful diagnostic imaging examination for the breast, the lung and orthopedics. However the size of the reconstructed region is limited by the mechanical acquisition motion of the X-ray tube and image detector so it is not possible to generate long view images for the spinal columns or the lower limbs examinations. Long-View Tomosynthesis (LVTS) method uses a different acquisition motion and post processing algorithm but results in a similar high resolution image slice free of anatomy above and below slice of interest. This method consists of three steps. First, acquire multi images while X-ray tube and Flat Panel Detector (FPD) are moving continuously in same linear direction. Then each image is divided into strips and strips from different images having similar X-ray beam trajectory are stitched together. Then multi slice coronal images are reconstructed from the long stitched images using filtered backprojection technique (FBP) which is similar to reconstruction algorithms used with Computed Tomography (CT) and TS. As a result, LVTS has 1.6 cycle/mm spatial resolution and 432[mm] × 800[mm] image size at a maximum. We conclude that LVTS improves depiction of long view tomograms, which can not be acquired by TS. Like TS, LVTS can produce images for weight bearing or partial weight bearing anatomy that is not possible with CT since LVTS has been integrated onto a tilting table.

For the last few years, development and optimization of three-dimensional (3D) x-ray breast imaging systems, such as breast tomosynthesis and computed tomography, has drawn much attention from the medical imaging community, either academia or industry. However, the trade offs between patient safety and the efficacy of the devices have yet to be investigated with use of objective performance metrics. Moreover, as the 3D imaging systems give depth information that was not available in planar mammography, standard mammography quality assurance and control (QA/QC) phantoms used for measuring system performance are not appropriate since they do not account for background variability and clinically relevant tasks. Therefore, it is critical to develop QA/QC methods that incorporate background variability with use of a task-based statistical assessment methodology.¹ In this work, we develop a physical phantom that simulates variable backgrounds using spheres of different sizes and densities, and present an evaluation method based on statistical decision theory,² in particular, with use of the ideal linear observer, for evaluating planar and 3D x-ray breast imaging systems. We demonstrate our method for a mammography system and compare the variable phantom case to that of a phantom of the same dimensions filled with water. Preliminary results show that measuring the system's detection performance without consideration of background variability may lead to misrepresentation of system performance.

Tomosynthesis is an imaging technique that has gained renewed interest with recent advancements of flat-panel digital detectors. Because of the wide range of potential applications, a systematic analysis of 3D tomosynthesis imaging systems would contribute to the understanding and development. This paper extends a systematic evaluation of thoracic tomosynthetic imaging performance as a function of imaging parameters, such as the number of projections, tomosynthesis orbital extent, and reconstruction filters. We evaluate lung nodule detectability and anatomical clutter as a function of tomosynthesis orbital extent using anthropomorphic phantoms and a table-top acquisition system. Tomosynthesis coronal slices were reconstructed using the FDK algorithm for cone-beam geometry from 91 projections uniformly distributed over acquisition orbital extents (θ) ranging from 10° to 180°. Visual comparisons of different tomosynthesis reconstructions of a lung nodule show the progressive decrease of anatomical clutter as θ increases. Additionally, three quantitative figures of merit were computed and compared: signal-difference-to-noise ratio (SDNR), anatomical clutter power spectrum (PS), and theoretical detectability index (DI). Lung nodule SDNR increases as θ increases from 0° to 120°. Anatomical clutter PS shows that the clutter magnitude and correlation decrease as θ increases, increasing detectability. Similarly, 2D and 3D DI increase as θ increases in the anatomical dominated exposure ranges. On the other hand, 2D slice DI is lower than the 3D DI for larger θ (e.g. 120°), because of the information loss in the depth direction for 2D slices. In other words, inspecting 3D is better for larger acquisition orbital extents, because the extra information acquired at larger angles cannot be fully recovered from 2D tomosynthesis reconstruction slices. In summary, detectability in tomosynthesis reconstructions for thoracic imaging increases as fixed dose is distributed over a larger acquisition orbital extent (up to 120°).

Hard X-ray phase-contrast imaging has been a hot research field in the last decade. It can provide high sensitivity of weakly absorbing low-Z objects in medical and biological fields. Grating-based differential phase-contrast (DPC) method has been paid more attention to because it can work with conventional X-ray tube and shows great potential for clinic application. Tomosynthesis with the combination of phase-contrast imaging is considered as a promising imaging method which can significantly enhance the contrast of low absorbing tissues and eliminate the effects of superimposed tissue on anatomical structures and is especially useful for medical applications such as mammography. In this paper, an experimental phase-contrast tomosynthesis system is implemented based on a weakly coherent hard X-ray phase-contrast method proposed by our group recently. The effectiveness of the proposed method is proved by actual experiments. Multiple information (absorption, refraction and dark-field) of the samples can be retrieved in one single imaging process by information retrieving methods. Then tomosynthesis reconstructions can be performed based on the retrieved information. It can eliminate the overlap of the sample structures and provide more extensive image information compared with conventional tomosynthesis.

We present data on a first prototype for photon counting tomosynthesis imaging of small children, which we call photoncounting tomosynthesis (PCT). A photon counting detector can completely eliminate electronic noise, which makes it ideal for tomosynthesis because of the low dose in each projection. Another advantage is that the detector allows for energy sensitivity in later versions, which will further lower the radiation dose. In-plane resolution is high and has been measured to be 5 lp/mm, at least 4 times better than in CT, while the depth resolution was significantly lower than typical CT resolution. The image SNR decreased from 30 to 10 for a detail of 10 mm depth in increasing thickness of PMMA from 10 to 80 mm. The air kerma measured for PCT was 5.2 mGy, which leads to an organ dose to the brain of approximately 0.7 mGy. This dose is 96 % lower than a typical CT dose. PCT can be appealing for pediatric imaging since young children have an increased sensitivity to radiation induced cancers. We have acquired post mortem images of a newborn with the new device and with a state-of-the-art CT and compared the diagnostic information and dose levels of the two modalities. The results are promising but more work is needed to provide input to a next generation prototype that would be suitable for clinical trials.

In limited angular aperture tomosynthesis systems, the addition of new degrees of freedom for data acquisition, such as angular aperture and sampling, requires specific optimizations. Typical optimization criteria include MTF, SNR, and NEQ. However, the strong anisotropy of the sampling frequency on the zaxis is usually neglected. Considering the signal in slices as the information contained within the volume defined by the slice plane and the z-sampling interval, the MTF of the reconstruction is obtained by integrating reconstruction blur within the slice. The relationship between z-sampling and aperture is proposed in terms of preservation of the DQE.

To achieve good image quality for computed tomography, it is important to accurately know the geometrical relationship between the X-ray source, the axis of rotation, and all of the detector channels. This usually involves knowing gross parameters such as iso-ray coordinate, detector pixel pitch, and source-to-detector distance, but for some detector types such as distorted arrays, polygonal or tiled arrays, or arrays of irregularly placed sparse detectors, it is beneficial to measure a more detailed description of the individual channel locations. Typically, geometric calibration and distortion calibration are performed using specialized phantoms, such as a pin, an array of pellets, or a wire grid, but these can have their practical downsides for certain applications. A promising recent alternative is to calibrate geometry in a way that requires no particular phantom or a priori knowledge of the scanned object -- these approaches are particularly helpful for high magnifications, large heavy objects, frequent calibration, and retrospective calibration. However, until now these approaches have only addressed gross geometry. In this paper, a framework is given which allows one to calibrate both gross and fine geometry from unknown objects. Example images demonstrate the success of the proposed methods on both real and simulated data.

We study a class of binary matrices with excellent noise properties for controlling multiplexing patterns in a multiple-source, single-detector X-ray system. For such a system, turning multiple sources on at a time in a prescribed pattern (multiplexing), can offer noise advantages under certain conditions. The patterns used can be represented by binary matrices which determine the noise properties of the decoded images. Hadamard S-matrices have long been used in spectroscopy, but they are optimal only in systems with little photonic noise. In X-ray systems with energy-integrating detectors, the noise structure may be a mix of constant (electronic) noise and noise proportional to the signal (photonic noise). Under mixed noise conditions, we demonstrate that a certain class of balanced incomplete block design (BIBD) matrices offers better noise performance over a wider range of noise mixes than the Hadamard matrices. Symmetric BIBD matrices are characterized by three parameters: v = the number of sources in the multiplexing array; k = the number of sources on at a time; and λ = the number of multiplexed frames shared by any pair of sources. We compare noise performance in decoded images for several families of BIBD matrices and show that the BIBD matrices with λ = 1 offer the best performance. We also offer insight into how the available matrices affect parameters of system design in a multiplexing X-ray system. We conclude that the BIBD(v,k,λ = 1) matrices or matrices derived from them are the best choices for multiplexing in multi-source X-ray systems.

In this paper, we demonstrate a methodology for quantitative evaluation of noise reduction algorithms for very low-dose (1/10th typical dose) renal CT perfusion imaging. Three types of noise reduction algorithms are evaluated, including the commonly used low pass filtering, edge-preserving algorithms, and spatial-temporal filtering algorithms, such as recently introduced local highly constrained back projection (HYPR-LR) technique and multi-band filtering (MBF). The performance of these noise reduction methods was evaluated in terms of background signal-to-noise ratio (SNR), spatial resolution, fidelity of the time-attenuation curves of renal cortex, and computational speed. The spatial resolution was quantified by an on-scene modulation transfer function (MTF) measurement method. The fidelity of time-attenuation curves was quantified by statistical analysis using a Chi-square test. The results indicate that algorithms employing spatial-temporal correlations of images, such as HYPR and MBF, can achieve spatial resolution similar to the images acquired using routine dose levels. Edge-preserving algorithms, such as anisotropic diffusion and bilateral filtering, also show good performance in terms of background SNR and spatial resolution, but they are rather slow compared to HYPR and MBF. However, edge-preserving algorithms can be applied in the situations where images do not have strong spatial-temporal correlation. Finally, all the noise reduction algorithms show a high fidelity of the time-attenuation curves, which can be explained by a strong iodine attenuation signal in the highly perfused kidney.

Interfraction motion of a treatment target such as the prostate in radiation therapy (RT) is, in part, responsible for large planning target volume (PTV) margins and related side effects. Online adjustment of the treatment based on timely cone-beam CT (CBCT) images can be particularly useful for patients with large interfraction motion. However, radiation dose to the patient due to frequent CBCT poses a radiation safety concern. One unique feature of CBCT for interfraction motion detection is the availability of a prior anatomical image most of which has not changed. We propose an iterative algorithm, for image reconstruction from a very limited number of projections in CBCT, that is based on total variation (TV) minimization subject to the constraints of data fidelity and positivity and that utilizes anatomical image prior information. Numerical studies for a 2D fan-beam geometry suggests the proposed algorithm can potentially contribute to lowering the radiation dose to the patient by allowing satisfactory image reconstruction from a very limited number of projections.

To perform a perspective cone-beam backprojection of the Feldkamp-type (FDK) the geometry of the approximately circular scan trajectory has to be available. If the system or the scan geometry is unknown and afflicted with geometric instabilities (misalignment) reconstructing a misaligned scan can cause severe artifacts in the CT images. We propose an online and image-based iterative correction of a misaligned reconstruction geometry by using entropy minimization. Unlike current methods which use a calibration of the geometry for defined scan protocols and calibration phantoms, the proposed method is performed combining a simplex algorithm for multi-parameter optimization and a graphics card (GPU)-based FDK-reconstruction in an iterative scheme. The simplex algorithm changes the geometric parameters of source and detector with respect to the reduction of entropy. In order to reduce the size of the dimensional space required for minimization the trajectory described by a subset of trajectory points. A virtual trajectory of an approximately circular path is generated after each iteration of the algorithm. This method was validated using simulations and measurements performed on a Carm CT System equipped with a flat-panel detector (Axiom Artis, Siemens Healthcare, Forchheim, Germany). Entropy was minimal for the ideal dataset, whereas strong misalignment resulted in a higher entropy value. The use of the GPU-based reconstruction provided an online geometry correction after a total computation time of only 1-3 s using 100 to 300 iterations of the algorithm, depending on the degree of misalignment and initialization conditions.

This paper presents an iterative method for compensation of motion artifacts for slowly rotating computed tomography (CT) systems. The inconsistencies among projections introduce severe reconstruction artifacts for free breathing acquisitions. Streaks and false structures appear and the resolution is limited by strong blurring. The rationale of the motion compensation method is to iteratively correct the reconstructed image by first extracting the motion artifacts in projection space, then reconstructing the artifacts in image space, and finally subtracting the artifacts from the original reconstruction. The perceived motion is extracted in projection space from the difference between acquired and reference projections, sampled from the image reconstructed in a previous iteration step. The initial image is reconstructed from acquired data and is nevertheless considered as the reference, although it contains artifacts. This image is iteratively corrected by subtraction of the estimated motion artifacts. The originality of the technique stems from the fact that the patient motion is not estimated but the artifacts are reconstructed in image space. It can provide sharp static anatomical images on slowly rotating on-board imagers in radiotherapy or interventional C-arm systems. Qualitative and quantitative figures are shown for experiments based on simulated projections of a sequence of clinical images resulting from a respiratory-gated helical CT acquisition. The border of the diaphragm becomes sharper and the contrast improves for small structures in the lungs.

A method to remove stents and consequently to eliminate the blooming artifacts off the stents is proposed in dual energy CT. The method could also reduce the blooming artifacts off calcified plaques. A phantom study is performed to test the method. The phantom consists of a stainless steel stent and a dumbbell shaped plastic (Delrin) cylinders. With the dual energy technique and the knowledge of the stent material, we separate the stent from the Delrin at each image voxels accurately. The large and small diameters of the Delrin are measured from the images by the full width at half maximum as 2.8 mm and 1.4 mm, respectively. They are very close to the true values of 2.4 mm and 1.2 mm. By respectively discarding even and odd view data for the low and high voltages, we simulate the fast kV-switching acquisitions where one view mis-registration exists between the low/high voltage scans. Comparing with the original images by the slow kV-switching where a perfect registration is realized between the low/high voltage scans, the images from the fast kVswitching show no significant differences except for the noise pattern.

Under normal circumstances the quality of images reconstructed with the classic FBP CT reconstruction algorithm is adequate for medical diagnosis. However, in some special cases the assumptions made by this method are not applicable because of non-linearities in the underlying physical imaging processes. Especially in the presence of metal implants in the field of view, effects like beam hardening, scatter and photon starvation result in serious streaking and banding artifacts around and between these objects. In order to reduce the artifacts, several different types of correction methods were introduced during the last two decades. In one of the most often used approaches, an interpolation scheme is used to replace all corrupted beam data in the shadow of the metal with artificially generated values. Although this leads to a reduction of the most severe artifacts, typically the results are far from being perfect. Instead of removing all artifacts, in most cases new streak artifacts are introduced. In the present work it is shown that the origin of these new artifacts is related to the loss of edge information of the objects by using surrogate data. The application of a more sophisticated artifact reduction method based on a segmentation of a preliminary reconstructed image decreases the number of newly introduced artifacts to a large degree. This is possible, because edge information between air and tissue recovered from the preliminary reconstruction can be included into the correction scheme. It is concluded that a restoration scheme without additionally information is not sufficient for a successful metal artifact reduction method.

X-ray cone-beam (CB) projection data often contain high amounts of scattered radiation, which must be properly modeled in order to produce accurate computed tomography (CT) reconstructions. A well known correction technique is the scatter kernel superposition (SKS) method that involves deconvolving projection data with kernels derived from pencil beam-generated scatter point-spread functions. The method has the advantages of being practical and computationally efficient but can suffer from inaccuracies. We show that the accuracy of the SKS algorithm can be significantly improved by replacing the symmetric kernels that traditionally have been used with nonstationary asymmetric kernels. We also show these kernels can be well approximated by combinations of stationary kernels thus allowing for efficient implementation of convolution via FFT. To test the new algorithm, Monte Carlo simulations and phantom experiments were performed using a table-top system with geometry and components matching those of the Varian On-Board Imager (OBI). The results show that asymmetric kernels produced substantially improved scatter estimates. For large objects with scatter-to-primary ratios up to 2.0, scatter profiles were estimated to within 10% of measured values. With all corrections applied, including beam hardening and lag, the resulting accuracies of the CBCT reconstructions were within ±25 Hounsfield Units (±2.5%).

Recently, we developed an efficient scatter correction method for x-ray imaging using primary modulation. A two-dimensional (2D) primary modulator with spatially variant attenuating materials is inserted between the x-ray source and the object to separate primary and scatter signals in the Fourier domain. Due to the high modulation frequency in both directions, the 2D primary modulator has a strong scatter correction capability for objects with arbitrary geometries. However, signal processing on the modulated projection data requires knowledge of the modulator position and attenuation. In practical systems, mainly due to system gantry vibration, beam hardening effects and the ramp-filtering in the reconstruction, the insertion of the 2D primary modulator results in artifacts such as rings in the CT images, if no post-processing is applied. In this work, we eliminate the source of artifacts in the primary modulation method by using a one-dimensional (1D) modulator. The modulator is aligned parallel to the ramp-filtering direction to avoid error magnification, while sufficient primary modulation is still achieved for scatter correction on a quasicylindrical object, such as a human body. The scatter correction algorithm is also greatly simplified for the convenience and stability in practical implementations. The method is evaluated on a clinical CBCT system using the Catphan© 600 phantom. The result shows effective scatter suppression without introducing additional artifacts. In the selected regions of interest, the reconstruction error is reduced from 187.2HU to 10.0HU if the proposed method is used.

It is well known that decomposing an object into attenuation or material basis functions provides additional imaging benefits such as contrast enhancement or material subtraction. This can be accomplished with photon counting x-ray detectors (PCXDs) with energy discriminating capabilities, which enable us to count x-ray photons and classify them based on their energies. The richness of the information contained in these measurements can depend heavily on how these photons are binned together. In this paper, our goal is to identify a method that yields the optimal energy thresholds and/or weights for binning data from energy discriminating PCXDs. Additional energy information from these PCXDs allows us to use maximum-likelihood to estimate the amount of the basis materials penetrated by the beam. However, due to inherent quantum noise, these estimates are themselves noisy. We show that for PCXDs that discriminate between low and high energy photons, it is beneficial to have a gap between the thresholds. Photons with energies that fall into this gap should either be discarded or counted separately to improve material separability. Furthermore, if the PCXD can discern the energy of each photon, we show that when estimating the amount of each of two material basis functions, two appropriately weighted sums of the photon counts provide as much information as knowing the number of counts at each energy.

This paper presents a progress update with the development of a distributed x-ray source. We present a high level summary of the source integration, simulation and experimental results, as well as challenges in electron beam focusing, beam current gating, voltage isolation, and anode technologies. We present focal spot measurements, x-ray images and a summary of our distributed x-ray source concept.

The multi-source Inverse-Geometry CT(MS-IGCT) system uses a 2D array of sources opposite a smaller 2D detector array. One sample system design uses 3 rows of 21 sources each. Because the MS-IGCT system provides sufficient sampling in the axial direction, cone beam artifacts can be reduced. Projection data from the 21 sources at the same zlocation can be rebinned into one cone beam projection, therefore, we can have 3 different cone beam projection data sets after rebinning, and reconstruction can be performed by using the FDK algorithm. However, if FDK is used, each of the three data sets by itself produces different cone beam artifacts. For example, the upper sources can provide artifact free images in the upper reconstruction volume, but cone beam artifacts can be observed in the central and lower reconstruction volume. The central and lower sources also provide artifact free image at different z-locations. We can achieve an artifact free volume by using artifact free images at different z-locations. However, if we could use all the data, the SNR can be improved. In this study, we develop a method to combine reconstructed volumes in Fourier space, and the main goal is to keep the exactness and improve the SNR in the combined image. The method was tested with a simulation of a Defrise phantom and the proposed method did not show cone beam artifacts. A noise simulation was also performed by using ideal bowtie filter so that all projection data had the same noise level. A noise simulation showed that the noise variance was ~1/3 of that in a single FDK reconstruction.

We report on a characterization study of a multi-row direct-conversion x-ray detector used to generate the first photon counting clinical x-ray computed tomography (CT) patent images. In order to provide the photon counting detector with adequate performance for low-dose CT applications, we have designed and fabricated a fast application specific integrated circuit (ASIC) for data readout from the pixellated CdTe detectors that comprise the photon counting detector. The cadmium telluride (CdTe) detector has 512 pixels with a 1 mm pitch and is vertically integrated with the ASIC readout so it can be tiled in two dimensions similar to those that are tiled in an arc found in 32-row multi-slice CT systems. We have measured several important detector parameters including the maximum output count rate, energy resolution, and noise performance. Additionally the relationship between the output and input rate has been found to fit a non-paralyzable detector model with a dead time of 160 nsec. A maximum output rate of 6 × 10⁶ counts per second per pixel has been obtained with a low output x-ray tube for CT operated between 0.01 mA and 6 mA at 140 keV and different source-to-detector distances. All detector noise counts are less that 20 keV which is sufficiently low for clinical CT. The energy resolution measured with the 60 keV photons from a ²⁴¹Am source is ~12%. In conclusion, our results demonstrate the potential for the application of the CdTe based photon counting detector to clinical CT systems. Our future plans include further performance improvement by incorporating drift structures to each detector pixel.

X-ray detectors made of crystalline silicon have several advantages including low dark currents, fast charge collection and high energy resolution. For high-energy x-rays, however, silicon suffers from its low atomic number, which might result in low detection efficiency, as well as low energy and spatial resolution due to Compton scattering. We have used a monte-carlo model to investigate the feasibility of a detector for pediatric CT with 30 to 40 mm of silicon using x-ray spectra ranging from 80 to 140 kVp. A detection efficiency of 0.74 was found at 80 kVp, provided the noise threshold could be set low. Scattered photons were efficiently blocked by a thin metal shielding between the detector units, and Compton scattering in the detector could be well separated from photo absorption at 80 kVp. Hence, the detector is feasible at low acceleration voltages, which is also suitable for pediatric imaging. We conclude that silicon detectors may be an alternative to other designs for this special case.

Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they provide accurate physical noise modeling. The newly developed compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. In x-ray CT reconstructions, the CS algorithm can be implemented in the statistical reconstruction framework. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least square and q-GGMRF) to the CS algorithm. In assessing the image quality using these non-linear reconstructions it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. A quality factor which accounts for the noise performance and the spatial resolution was introduced to objectively evaluate the performance of the algorithm under two conditions: 1) constant undersampling factor comparing different algorithms at different dose levels and 2) varying undersampling factors and dose levels for the CS algorithm. To facilitate this comparison the original CS method was also formulated in the framework of the statistical image reconstruction algorithm. This is also a novel aspect of this work. Important conclusions of the measurements are that: for realistic anatomy over 100 projections are needed to avoid streak artifacts even with CS reconstruction, regardless of the algorithm employed it is beneficial to distribute the total dose to many views as long as each view remains quantum noise limited, and the CS method is not appropriate for low dose levels because while it can mitigate streaking artifacts the images being to exhibit a patchy behavior.

We investigate an algorithm for boundary-enhanced image reconstruction from limited-angle projection data in X-ray phase-contrast tomography. The algorithm exploits the fact that the imaging model of phase-contrast tomography establishes a sparse representation of the object that facilitates accurate image reconstruction form highly incomplete measurement data. The developed algorithm may therefore benefit a wide range of X-ray phase-contrast tomography applications by dramatically reducing data-acquisition times and limiting radiation dose.

This work studies the dual formulation of a penalized maximum likelihood reconstruction problem in x-ray CT. The primal objective function is a Poisson log-likelihood combined with a weighted cross-entropy penalty term. The dual formulation of the primal optimization problem is then derived and the optimization procedure outlined. The dual formulation better exploits the structure of the problem, which translates to faster convergence of iterative reconstruction algorithms. A gradient descent algorithm is implemented for solving the dual problem and its performance is compared with the filtered back-projection algorithm, and with the primal formulation optimized by using surrogate functions. The 3D XCAT phantom and an analytical x-ray CT simulator are used to generate noise-free and noisy CT projection data set with monochromatic and polychromatic x-ray spectrums. The reconstructed images from the dual formulation delineate the internal structures at early iterations better than the primal formulation using surrogate functions. However the body contour is slower to converge in the dual than in the primal formulation. The dual formulation demonstrate better noise-resolution tradeoff near the internal organs than the primal formulation. Since the surrogate functions in general can provide a diagonal approximation of the Hessian matrix of the objective function, further convergence speed up may be achieved by deriving the surrogate function of the dual objective function.

CT imaging is useful and ubiquitous. There is, however, a desire to reduce imaging artifacts, improve resolution, while reducing radiation. Iterative reconstruction algorithms have been proposed as one approach towards achieving these goals. In this paper we compare phantom images produced using commercial FBP-based reconstruction to three different iterative algorithms. We focus specifically on statistical characterizations of the noise, both at full radiation dose and at 50% dose. An iterative algorithm which segregates the image into two components (soft tissue and dense object), and imposes different constraints on these components, yielded better noise characteristics than ART, total variation, and FBP.

We offer a novel approach for real-time CT reconstruction with the possibility of interactively changing parameters like the position and orientation of the slice to arbitrary values by the user during the analysis. To achieve this, a new reconstruction, including backprojection, is done every time the user wants to see a different view (in contrast to computing a volume upfront). The reconstruction was implemented on a GPU (graphics processing unit) using OpenGL and provides near real-time performance with less than 20 ms reconstruction time for 512 × 512 images. With this approach the user is free to change parameters that are fixed when a conventional reconstruction is used. So he is free to set the position of the slice, its orientation and the voxel size to arbitrary values, or to select a different set of projections for a cardiac reconstruction. Thus the waiting time for the volume reconstruction is removed. Therefore our method is esp. promising for applications such as intra-operative CT and interventional CT.

The Common Unified Device Architecture (CUDA) introduced in 2007 by NVIDIA is a recent programming model making use of the unified shader design of the most recent graphics processing units (GPUs). The programming interface allows algorithm implementation using standard C language along with a few extensions without any knowledge about graphics programming using OpenGL, DirectX, and shading languages. We apply this novel technology to the Simultaneous Algebraic Reconstruction Technique (SART), which is an advanced iterative image reconstruction method in cone-beam CT. So far, the computational complexity of this algorithm has prohibited its use in most medical applications. However, since today's GPUs provide a high level of parallelism and are highly cost-efficient processors, they are predestinated for performing the iterative reconstruction according to medical requirements. In this paper we present an efficient implementation of the most time-consuming parts of the iterative reconstruction algorithm: forward- and back-projection. We also explain the required strategy to parallelize the algorithm for the CUDA 1.1 and CUDA 2.0 architecture. Furthermore, our implementation introduces an acceleration technique for the reconstruction compared to a standard SART implementation on the GPU using CUDA. Thus, we present an implementation that can be used in a time-critical clinical environment. Finally, we compare our results to the current applications on multi-core workstations, with respect to both reconstruction speed and (dis-)advantages. Our implementation exhibits a speed-up of more than 64 compared to a state-of-the-art CPU using hardware-accelerated texture interpolation.

In scintillating detectors x-rays are converted to luminescent photons with a time delay. The corresponding time resolution of the detector can have - in contrast to usual multi-slice CT - a deteriorating effect in new CT concepts with multiple sources illuminating one detector, because x-ray intensities measured here in consecutive projections correspond to the absorption along paths through very different regions of the object. A new analytical description of these effects is presented and a correction algorithm is derived. It is also shown that the detector time delay and its correction can lead to a noticeable increase of image noise.

There are growing interests in using cone-beam computed tomography (CBCT) for patient treatment position setup and dose evaluation in radiation therapy. The repeated use of CBCT during the course of a treatment has raised concerns of extra radiation dose delivered to patients. One way to reduce radiation dose delivered to patients during CBCT procedure is to acquire CT projection data with a lower mAs level. However, the image quality of the projection image and the reconstructed CBCT image will degrade due to excessive quantum noise as a result of low mAs protocol. In this work, we first studied the noise properties of CBCT projection data from repeated scan and then improved low-dose CBCT image quality by restoring CBCT projection images based on an improved noise model of CBCT projection data. Analysis of repeated measurements show that noise is correlated among nearest neighbors in projection data, i.e., covariance matrix of projection data noise is non-diagonal. The covariance matrix of noise provides the knowledge of second-order statistics of noise, which may lead to more accurate estimation for statistical image reconstruction and restoration algorithm. We constructed the penalized weighted least-squares (PWLS) objective function by incorporating the noise correlation of CBCT projection data. The optimal solution of the line integrals is then estimated by minimizing the PWLS objective function. A quality assurance phantom was used to evaluate the presented algorithm for noise reduction in low-dose CBCT.

For accurate CT reconstruction, it is important to know the geometric position of every detector channel relative to the X-ray source and the rotation axis. Often, such as for truly equally spaced detectors, it may suffice just to accurately know the gross geometry. However, for some detector designs, a detailed description of the fine-scale channel locations may also be necessary. While there are numerous methods to perform fine-scale calibration, such methods generally assume a continuous distortion (typically for image intensifiers) and are thus unsuitable for detectors with discrete distortions such as irregularly placed discrete sensors, tiled flat panels, or multiple flat segments arranged to form a polygonal approximation to an arc. In this paper, a method is proposed to measure both gross and fine geometry from a single simple calibration scan in a way that properly characterizes discrete irregularities. Experimental results show the proposed method to be rather effective on polygonal arrays. While the method is derived and demonstrated for fan beam, a discussion is given on extending it to cone beam CT.

Simultaneous reconstruction of activity and attenuation in positron emission tomography without transmission data presents significant degradation due to crosstalk effect. The objective of this work is to investigate the effect of applying a priori knowledge, such as known attenuation coefficients, in some regions of the image, into a simultaneous activity and attenuation reconstruction algorithm (EM-AA). The methodology consists of applying, after each iteration, a global correction (addition) on the attenuation map, based on the difference between the known attenuation coefficient and the average of the estimated coefficients in the region. We also applied a correction factor that decreases with iteration number. The assessments were carried out via phantoms emulating 3D PET that presented specific features for crosstalk and structural accuracy measurements. We obtained three figures of merit for activity and three for attenuation. The results showed that, in the case of noiseless projections, the proposed correction improved the estimation of both activity and attenuation. On the other hand, while structural accuracy improved with iterations, the crosstalk effects become worse. The improvements were more pronounced for structural accuracy than for crosstalk effects. However, the errors are still too high, and more research is needed in this area.

Compression of computed tomography (CT) projection samples reduces slip ring and disk drive costs. A lowcomplexity, CT-optimized compression algorithm called Prism CT^TM achieves at least 1.59:1 and up to 2.75:1 lossless compression on twenty-six CT projection data sets. We compare the lossless compression performance of Prism CT to alternative lossless coders, including Lempel-Ziv, Golomb-Rice, and Huffman coders using representative CT data sets. Prism CT provides the best mean lossless compression ratio of 1.95:1 on the representative data set. Prism CT compression can be integrated into existing slip rings using a single FPGA. Prism CT decompression operates at 100 Msamp/sec using one core of a dual-core Xeon CPU. We describe a methodology to evaluate the effects of lossy compression on image quality to achieve even higher compression ratios. We conclude that lossless compression of raw CT signals provides significant cost savings and performance improvements for slip rings and disk drive subsystems in all CT machines. Lossy compression should be considered in future CT data acquisition subsystems because it provides even more system benefits above lossless compression while achieving transparent diagnostic image quality. This result is demonstrated on a limited dataset using appropriately selected compression ratios and an experienced radiologist.

Perfusion imaging is often used for diagnosis and for assessment of the response to the treatment. If perfusion can be measured during interventional procedures, it could lead to quantitative, more efficient and accurate treatment; however, imaging modalities that allow continuous dynamic scanning are not available in most of procedure rooms. Thus, we developed a method to measure the perfusion-time attenuation curves (TACs)-of regions-of-interest (ROIs) using xray C-arm angiography system with no gantry rotation but with a priori. The previous study revealed a problem of large oscillations in the estimated TACs and the lack of comparison with CT-based approaches. Thus the purposes of this study were (1) to reduce the variance of TDCs; and (2) to compare the performance of the improved PAP with that of the CT-based perfusion method. Our computer simulation study showed that the standard deviation of PAP method was decreased by 10.7-59.0% and that it outperformed (20× or 200× times) higher dose CT methods in terms of the accuracy, variance, and the temporal resolution.

As multi-slice CT develops, there are great expectations for an automatic and computer-support diagnoses. This research is on bronchial area which is composed of the bronchial wall regions and the air regions in the internal bronchial tube. Since to diagnose this is difficult, support diagnosis using CT images is desired. The thickness of bronchial wall changes as the airway of early lung cancer, bronchial asthma and the bronchial enhancing syndrome and others change into a malignant state. These changes are detected and the thickness of bronchial wall becomes important information. In this research, the extraction accuracy of the algorithm for bronchial wall evaluation is good.

We discuss the ongoing development of soft-tissue imaging capabilities on xCAT, a highly portable, flat-panel based cone-beam X-ray CT platform. By providing the ability to rapidly detect intra-cranial bleeds and other symptoms of stroke directly at the patient's bedside, our new system can potentially significantly improve the management of neurological emergency and intensive care patients. The paper reports on the design of our system, as well as on the methods used to combat artifacts due to scatter, non-linear detector response and scintillator glare. Images of cadaveric head samples are also presented and compared with conventional CT scans.

We have designed and built a stationary digital breast tomosynthesis (DBT) system containing a carbon nanotube based field emission x-ray source array to examine the possibility of obtaining a reduced scan time and improved image quality compared to conventional DBT systems. There are 25 individually addressable x-ray sources in our linear source array that are evenly angularly spaced to cover an angle of 48°. The sources are turned on sequentially during imaging and there is no motion of either the source or the detector. We present here an iterative reconstruction method based on a modified Ordered-Subset Convex (MOSC) algorithm that was employed for the reconstruction of images from the new DBT system. Using this algorithm based on a maximum-likelihood model, we reconstruct on non-cubic voxels for increased computational efficiency resulting in high in-plane resolution in the images. We have applied the reconstruction technique on simulated and phantom data from the system. Even without the use of the subsets, the reconstruction of an experimental 9-beam system with 960×768 pixels took less than 6 minutes (10 iterations). The projection images of a simulated mammography accreditation phantom were reconstructed using MOSC and a Simultaneous Algebraic Reconstruction technique (SART) and the results from the comparison between the two algorithms allow us to conclude that the MOSC is capable of delivering excellent image quality when used in tomosynthesis image reconstruction.

This paper presents a new iterative motion correction technique composed of motion estimation in projection space, motion segmentation in image space, and motion compensation within an analytical filtered-backprojection (FBP) image reconstruction algorithm. The motion is estimated by elastic registration of acquired projections on reference projections. Reference projections are sampled from the image, reconstructed in a previous iteration step. To apply the motion compensation locally, the image regions significantly affected by motion are segmented. First the perceived motion is identified in projection space by computing the absolute difference between acquired line integrals and reference line integrals. Then, differences are reconstructed in image space, and the image is regularized with a pipeline of standard image processing operators. The result of this procedure is a normalized motion map, associating each image element with a measure of the local motion detected there. The estimated displacement vectors in projection space and the reconstructed motion map in image space are then used by an adaptive motion-compensated FBP algorithm to reconstruct a sharper image. Results are shown qualitatively and quantitatively for reconstructions from realistic projections, simulated from clinical patient data. Since the method does not assume any periodicity of the motion model, it can correct reconstruction artifacts due to unstructured patient motion, such as breath-hold failure, abdominal contractions, and nervous movements.

Computed Tomography (CT) is widely used in the modern clinical settings. In certain procedures, the region of interest (ROI) is often considerably smaller than the imaged field of view (FOV), thereby subjecting the patient to extra dose. For these procedures, we propose a method of filtered region-of-interest (FROI) CT. In this procedure, a predetermined ROI is imaged with standard x-ray intensity, while surrounding areas are imaged using a substantial lower x-ray intensity by interposing an x-ray attenuator in the beam. For the FROI-CT acquisitions in this study, a gadolinium filter with a circular central opening is placed in the x-ray beam of a standard clinical rotational angiography system. The resulting image contains a high intensity ROI, a low intensity region surrounding the ROI, and a transition region between these two. Three-dimensional reconstruction using these images would result in artifacts. Therefore, the intensities in the images are equalized prior to reconstruction. To equalize the intensities, first two images are obtained, one unfiltered and one with a filter in place. The corresponding data in the two images are used in a linear least-squares fit to determine the equalization function. The transition region is equalized using a radial filter technique, based on a comparison of the data on either side of the transition region after intensity equalization. The technique was evaluated using rotational angiographic sequences of a head phantom obtained with and without the filter in place. Differences between conventional (unfiltered) and FROI-equalized images of the head phantom were approximately 5%. Differences in reconstructed images (conventional and FROI) were 7% on average inside the reconstructed ROI. These results are comparable to those obtained for two separate standard acquisitions. A 50% dose reduction was obtained for a 50% FOV radius for the filter. These results indicate that FROI-CT can provide the physician with the image detail comparable to conventional image acquisition while reducing dose to the patient.

In the conventional single photon emission computed tomography (SPECT), reconstruction algorithm requires full projection data to reconstruct the images, which will be time-consuming. While in clinic, doctors usually just care about the region of interest (ROI), such as heart, not whole body, in this case, a local SPECT reconstruction algorithm is needed to reconstruct the ROI by only using the projection data from the ROI. In SPECT, the non-stationary Possion noise in the projection data (sinogram) is a major cause to compromise the quality of the reconstructed images. To improve the reconstruction quality, we must remove the Possion noise in the sinogram before reconstruction. However, the conventional space or frequency domain de-noising methods possibly remove the edge information, which is very important for the accurate reconstruction, especially for the local SPECT reconstruction with non-uniform attenuation. Wavelet transform, due to its excellent localization property, has rapidly become an indispensable image processing tool for de-noising. In this paper, we tried to find out the properties of wavelet based de-noising methods for local SPECT reconstruction with non-uniform attenuation. From the de-noising results, we can see that wavelet based de-noising methods have good performance for local SPECT reconstruction.

Signal and noise transfer properties of x-ray detectors are described by the detective quantum efficiency DQE. The DQE is a precise analysis tool, however, it is not meant to identify the various noise sources. The noise decomposition method is based on measured noise power spectra, following previous work by Mackenzie. Noise is distinguished by its variations with dose and spatial frequency: Quantum noise, fixed pattern noise, Lubberts noise, noise aliasing, and others. By determining all major noise sources, DQE results can be extrapolated within a precision of approximately 2% to other clinical relevant dose values that have not been measured. This precision shows an improvement to the method proposed by Mackenzie. The major noise sources are further sub-divided. For the calculation of noise sub-components a precision of 4% is achieved. The decomposition allows a detailed analysis of the dominant noise component in a certain dose or spatial frequency range, in particular the determination of spectral noise equivalent dose, the impact on DQE by different gain and offset correction schemes, and the influence of different scintillators on Lubberts noise.

Low pass filters can affect the quality of clinical SPECT images by smoothing. Appropriate filter and parameter selection leads to optimum smoothing that leads to a better quantification followed by correct diagnosis and accurate interpretation by the physician. This study aims at evaluating the low pass filters on SPECT reconstruction algorithms. Criteria for evaluating the filters are estimating the SPECT reconstructed cardiac azimuth and elevation angle. Low pass filters studied are butterworth, gaussian, hamming, hanning and parzen. Experiments are conducted using three reconstruction algorithms, FBP (filtered back projection), MLEM (maximum likelihood expectation maximization) and OSEM (ordered subsets expectation maximization), on four gated cardiac patient projections (two patients with stress and rest projections). Each filter is applied with varying cutoff and order for each reconstruction algorithm (only butterworth used for MLEM and OSEM). The azimuth and elevation angles are calculated from the reconstructed volume and the variation observed in the angles with varying filter parameters is reported. Our results demonstrate that behavior of hamming, hanning and parzen filter (used with FBP) with varying cutoff is similar for all the datasets. Butterworth filter (cutoff > 0.4) behaves in a similar fashion for all the datasets using all the algorithms whereas with OSEM for a cutoff < 0.4, it fails to generate cardiac orientation due to oversmoothing, and gives an unstable response with FBP and MLEM. This study on evaluating effect of low pass filter cutoff and order on cardiac orientation using three different reconstruction algorithms provides an interesting insight into optimal selection of filter parameters.

CT numbers of the spleen, liver, and trachea air were measured from non-contrast images obtained from 4-channel and 64-channel scanners from the same vendor. Image sections of 1 mm and 5 mm were reconstructed using smooth and sharp kernels. For spleen and liver, no significant differences associated with the variations in kernels or slice thickness could be demonstrated. The increase of the number of channels from 4 to 64 lowered the spleen CT numbers from 53 HU to 43 HU (p <0.00001). The 4-channel spleen CT numbers slightly increased as function of patient size, while the 64-channel CT numbers decreased as function of patient size. Linear regressions predicted for 40-cm patients the spleen 64-channel CT values were 23 HU lower than 4-channel CT numbers. The smooth kernel, 4-channel trachea air CT numbers had mean of -1004 +/-4.8 HU and the 64-channel trachea air CT numbers had a mean of -989+/-4.5 HU. The patient-size dependencies suggest that the CT attenuation variation is associated with increased scatter in 64-channel MSCT. Using CT number to distinguish solid lesions from cysts or quantitative evaluation of COPD disease using CT images may be complicated by inconsistencies between CT scanners.

An experimental cone-beam Micro-CT system for small animal imaging is presented in the paper. The system is designed to obtain high-resolution anatomic information and will be integrated with our bioluminescence tomography system. A flat panel X-ray detector (CMOS technology with a column CsI scintillator plate, 50 micron pixel size, 120 mm × 120 mm photodiode area) and a micro-focus X-ray source (13 to 40 μm of focal spot size) are used in the system. The object (mouse or rat) is placed on a three-degree (two translations and one rotation) programming stage and could be located to an accurate position in front of the detector. The large field of view (FOV) of the system allows us to acquire the whole body imaging of a normal mouse in one scanning which usually takes about 6 to 15 minutes. Raw data from X-ray detector show spatial variation caused by dark image offset, pixel gain and defective pixels, therefore data pre-processing is needed before reconstruction. Geometry calibrations are also used to reduce the artifacts caused by geometric misalignment. In order to accelerate FDK filtered backprojection method, we develop a reconstruction software using GPU hardware in our system. System spacial resolution and image uniformity and voxel noise have been assessed and mouse reconstruction images are illuminated in the paper. Experiment results show that this system is suitable for small animal imaging.

Quantitative in-vivo imaging of lung perfusion in rodents can provide critical information for preclinical studies. However, the combined challenges of high temporal and spatial resolution have made routine quantitative perfusion imaging difficult in rodents. We have recently developed a dual tube/detector micro-CT scanner that is well suited to capture first-pass kinetics of a bolus of contrast agent used to compute perfusion information. Our approach is based on the paradigm that the same time density curves can be reproduced in a number of consecutive, small (i.e. 50μL) injections of iodinated contrast agent at a series of different angles. This reproducibility is ensured by the high-level integration of the imaging components of our system, with a micro-injector, a mechanical ventilator, and monitoring applications. Sampling is controlled through a biological pulse sequence implemented in LabVIEW. Image reconstruction is based on a simultaneous algebraic reconstruction technique implemented on a GPU. The capabilities of 4D micro-CT imaging are demonstrated in studies on lung perfusion in rats. We report 4D micro-CT imaging in the rat lung with a heartbeat temporal resolution of 140 ms and reconstructed voxels of 88 μm. The approach can be readily extended to a wide range of important preclinical models, such as tumor perfusion and angiogenesis, and renal function.

With the online z-axis tube current modulation (OZTCM) technique proposed by this work, full automatic exposure control (AEC) for CT systems could be realized with online feedback not only for angular tube current modulation (TCM) but also for z-axis TCM either. Then the localizer radiograph was not required for TCM any more. OZTCM could be implemented with 2 schemes as attenuation based μ-OZTCM and image noise level based μ-OZTCM. Respectively the maximum attenuation of projection readings and standard deviation of reconstructed images can be used to modulate the tube current level in z-axis adaptively for each half (180 degree) or full (360 degree) rotation. Simulation results showed that OZTCM achieved better noise level than constant tube current scan case by using same total dose in mAs. The OZTCM can provide optimized base tube current level for angular TCM to realize an effective auto exposure control when localizer radiograph is not available or need to be skipped for simplified scan protocol in case of emergency procedure or children scan, etc.

For image-guided proton therapy, we investigated the feasibility of CBCT (cone-beam computed tomography) and CBDT (cone-beam digital tomosynthesis) technologies in the gantry treatment room. A fully equipped x-ray projection system, which was originally operated for patient alignment, in parallel to proton-beam direction was utilized for acquiring CBCT/CBDT. The performance of the imaging detector was analyzed in terms of MTF (modulation-transfer function), NPS (noise-power spectrum) and DQE (detective quantum efficiency). Tomographic imaging performances, such as spatial resolving power, linearity of CT numbers, SNR (signal-to-noise ratio), and CNR (contrast-to-noise ratio), were analyzed by using the AAPM (American Association of Physicists in Medicine) CT QC phantom. Geometric alignment of CBCT/CBDT system was analyzed by using a calibration phantom, which consists of steal ball bearings. The determined calibration parameters were applied to the image reconstruction procedures. The overall CBCT performances of the system were demonstrated with reconstructed humanoid phantom images. In addition, we implemented the CBDT with a selected number of projection views acquired for CBCT in limited angle ranges. From the reconstructed phantom images, the CBCT system in the gantry treatment room will be very useful as a primary patient alignment system for image-guided proton therapy. The CBDT may provide fast patient positioning with less motion artifact and patient doses.

We exploit the development of a clinical computed microtomography (micro-CT) system for dental imaging. While the conventional dental CT simply serves implant treatment, the clinical dental micro-CT may provide clinicians with a histologic evaluation. To investigate the feasibility of the realization of a dental micro-CT, we have constructed an experimental test system which mainly consists of a microfocus x-ray source, a rotational subject holder, and a flat-panel detector. The flat-panel detector is based on a matrix-addressed photodiode array coupled to a CsI:Tl scintillator. The detective quantum efficiency (DQE) of the detector was measured as a function of magnification based on the measured modulation-transfer function (MTF) and noise-power spectrum (NPS). The best MTF and DQE performances were achieved at the magnification factor of 3. Similar tendency of the spatial resolving power in tomography was also observed with a wire phantom having a 25 μm diameter. From the investigation of tomographs reconstructed from a humanoid skull phantom, the application of magnification in the system largely reduced both signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) for a fixed dose at the entrance surface of the detector, 1.2 mGy, while this setup increased the dose at the object plane from 4.7 mGy to 19.1 mGy for the magnification factor from 2 to 4, respectively. Although the quantum mottles at the high magnification factor tackled the practical use in the clinic, the information contained in the magnified CT images was quite promising.

In this study we theoretically investigated the minimum scan time of an inverse-geometry dedicated breast CT system that provides sufficient sampling and dose equivalent to mammography without exceeding the limits of source power or detector count rate. The inverse geometry, which utilizes a large-area scanned source and a narrower photon-counting detector, is expected to have improved dose efficiency compared to cone-beam methods due to reduced scatter effects and improved detector efficiency. The analysis assumed the specifications of available inverse-geometry source and detector hardware (SBDX, NovaRay, Inc, Newark CA). The scan time was calculated for a 10, 14, and 18-cm diameter breast composed of 50% glandular / 50% adipose tissue. The results demonstrate a minimum scan time of 6.5, 14.3, and 14.7 seconds for a 10, 14, and 18-cm-diameter breast, respectively. The scan times are comparable to those of proposed cone-beam systems. For all three breast sizes, the scan time was limited by the detector count rate. For example, for the 14-cm-diameter breast, the minimum scan time that met the source power limitation was 1.1 seconds, and the minimum scan time that achieved sufficient sampling was 0.8 seconds. The scan time can be reduced by increasing the detector count rate or area. Effective bowtie filters will be required to prevent detector saturation at the object edges. Overall, the results support preliminary feasibility of dedicated breast CT with an inverse geometry.

Mammography techniques have recently advanced from those using analog systems (the screen-film system) to those using digital systems; for example, computed radiography (CR) and flat-panel detectors (FPDs) are nowadays used in mammography. Further, phase contrast mammography (PCM)-a digital technique by which images with a magnification of 1.75× can be obtained-is now available in the market. We studied the effect of the air gap in PCM and evaluated the effectiveness of an antiscatter x-ray grid in conventional mammography (CM) by measuring the scatter fraction ratio (SFR) and relative signal-to-noise ratio (rSNR) and comparing them between PCM and the digital CM. The results indicated that the SFRs for the CM images obtained with a grid were the lowest and that these ratios were almost the same as those for the PCM images. In contrast, the rSNRs for the PCM images were the highest, which means that the scattering of x-rays was sufficiently reduced by the air gap without the loss of primary x-rays.

Single Mo target, Mo / Rh, or Mo / W bi-track targets with corresponding Mo and Rh filters have provided optimal target / filter combinations for traditional screen / film systems. In the advent of full-field digital mammography, similar target / filter combinations were adopted directly for digital imaging systems with direct and indirect conversion based detectors. To reduce the average glandular dose while maintaining the clinical image quality of FFDMs, alternative target / filter combinations have been investigated extensively to take advantages of the digital detectors with high dynamic range, high detection dose efficiency, and low noise level. This paper reports the development of a digital FFDM system that is equipped with single tungsten target and rhodium and silver filters. A mathematical model was constructed to quantitatively simulate x-ray spectra, breast compositions, contrast objects, x-ray scatter distribution, grid performance, and characteristics of a-Se flat panel detector. Computer simulations were performed to select kV/filter for different breast thickness and breast compositions through maximizing the contrast object detection dose efficiency. A set of phantom experiments were employed to optimize the x-ray techniques within the constraints of exposure time and required dose levels. A 50-micrometer rhodium filter was applied for thin and average breasts and a 50-micrometer silver filter for thicker breasts. To meet our design requirements and EUREF protocol specifications, we finely adjusted x-ray techniques for 0.45, 0.75, 1.0, 1.35 mGy dose modes with regards to ACR phantom scoring and PMMA phantom SNR/CNR performance, respectively. The optimal x-ray techniques significantly reduce average glandular dose while maintaining imaging performance.

To evaluate performance (image signal to noise ratio) of a digital mammographic system working in 2D planar versus tomosynthesis modality, a contrast detail phantom was developed embedding 1 cm plexyglas, including 49 holes of different diameter and depth, between two layers containing a breast simulating material. The acquisition protocol included 15 low dose projections (reconstructed 1mm-thick slices) and a 2D view. Using an automatic software analysis tool, the signal difference to noise ratio (SDNR) was evaluated. SDNR in the DBT images was about a factor two higher than with FFDM (P<1E-4). A more complete visual detection experiment is underway.

With increasing longitudinal detector dimension available in diagnostic volumetric CT, step-and-shoot scan is becoming popular for cardiac imaging. In comparison to helical scan, step-and-shoot scan decouples patient table movement from cardiac gating/triggering, which facilitates the cardiac imaging via multi-sector data acquisition, as well as the administration of inter-cycle heart beat variation (arrhythmia) and radiation dose efficiency. Ideally, a multi-sector data acquisition can improve temporal resolution at a factor the same as the number of sectors (best scenario). In reality, however, the effective temporal resolution is jointly determined by gantry rotation speed and patient heart beat rate, which may significantly lower than the ideal or no improvement (worst scenario). Hence, it is clinically relevant to investigate the behavior of effective temporal resolution in cardiac imaging with multi-sector data acquisition. In this study, a 5-second cine scan of a porcine heart, which cascades 6 porcine cardiac cycles, is acquired. In addition to theoretical analysis and motion phantom study, the clinical consequences due to the effective temporal resolution variation are evaluated qualitative or quantitatively. By employing a 2-sector image reconstruction strategy, a total of 15 (the permutation of P(6, 2)) cases between the best and worst scenarios are studied, providing informative guidance for the design and optimization of CT cardiac imaging in volumetric CT with multi-sector data acquisition.

Cardiac CT image reconstruction suffers from artifacts due to heart motion during acquisition. In order to mitigate these effects, it is common practice to choose a protocol with minimal gating window and fast gantry rotation. In addition, it is possible to estimate heart motion retrospectively and to incorporate the information in a motion-compensated reconstruction (MCR). If shape tracking algorithms are used for generation of the heart motion-vector field (MVF), the number and positions of the motion vectors will not coincide with the number and positions of the voxels in the reconstruction grid. In this case, data interpolation is necessary for MCR algorithms which require one motion vector at each voxel location. This work examines different data interpolation approaches for the MVF interpolation problem and the effects on the MCR results.

Rotational X-ray data acquisition in combination with gated reconstruction is applied most commonly to reconstruct 3D or 4D images of the heart on interventional X-ray systems. The data are acquired during breath hold and with intravenous contrast agent injection. Unfortunately, when using a single circular arc acquisition with parallel ECG recording, the gating of the projections leads to under-sampling artifacts in the reconstruction volume. In this contribution an artifact reduction method is suggested which is based on an initial gated reconstruction of a cardiac volume at limited quality, the subsequent segmentation of the volume and a second pass correction to enhance the signal-to-noise ratio in the reconstruction volume and to reduce the artifacts due to gating. The method is applied to both phantom and animal data.

Objective: To quantify the influence of velocity, calcification density and acquisition time on coronary calcium determination using multi-detector CT, dual-source CT and EBT. Materials and Methods: Artificial arteries with four calcifications of increasing density were attached to a robotic arm to which a linear movement was applied between 0 and 120 mm/s (step 10 mm/s). The phantom was scanned five times on 64-slice MDCT, DSCT and EBT using a standard acquisition protocol and the average Agatston score was determined. Results: Increasing motion artifacts were observed at increasing velocities on all scanners, with increasing severity from EBT to DSCT to 64-slice MDCT. The Agatston score showed a linear dependency on velocity from which a correction factor was derived. This correction factor showed a linear dependency on calcification density (0.92≤R²≤0.95). The slope and offset of this correction factor also showed a linear dependency on acquisition time (0.84≤R²≤0.86). Conclusion: The Agatston score is highly dependent on the average density of individual calcifications. The dependency of the Agatston score on velocity shows a linear behaviour on calcification density. A quantitative method could be derived which corrects the measured calcium score for the influence of velocity, calcification density and acquisition time.

Purpose: ECG-gated CTA allows visualization of the aneurysm and stentgraft during the different phases of the cardiac cycle, although with a lower SNR per cardiac phase than without ECG gating using the same dose. In our institution, abdominal aortic aneurysm (AAA) is evaluated using non-ECG-gated CTA. Some common CT scanners cannot reconstruct a non-gated volume from ECG-gated acquired data. In order to obtain the same diagnostic image quality, we propose offline temporal averaging of the ECG-gated data. This process, though straightforward, is fundamentally different from taking a non-gated scan, and its result will certainly differ as well. The purpose of this study is to quantitatively investigate how good off-line averaging approximates a non-gated scan. Method: Non-gated and ECG-gated CT scans have been performed on a phantom (Catphan 500). Afterwards the phases of the ECG-gated CTA data were averaged to create a third dataset. The three sets are compared with respect to noise properties (NPS) and frequency response (MTF). To study motion artifacts identical scans were acquired on a programmable dynamic phantom. Results and Conclusions: The experiments show that the spatial frequency content is not affected by the averaging process. The minor differences observed for the noise properties and motion artifacts are in favor of the averaged data. Therefore the averaged ECG-gated phases can be used for diagnosis. This enables the use of ECG-gating for research on stentgrafts in AAA, without impairing clinical patient care.

Dual-source computed tomography (CT) utilizes two x-ray tubes and two detectors simultaneously for the purpose of obtaining 83 msec temporal resolution, 160 kW of x-ray power reserve, or dual-kV (dual-energy) scan capabilities. One inherent constraint of such a design is cross-scatter radiation, which occurs when x-rays from tube A are scattered by the patient and detected by detector B, or vice versa. In the evaluated dual-source CT scanner, an on-line cross-scatter correction technique is used to address this limitation. The technique, available using the 14×1.2-mm collimation, measures scattered radiation along the z axis using detector rows beyond those corresponding to the 16.8 mm nominal total beam width. These direct measurements of scattered radiation are used to correct the measured projection data (scattered and primary radiation) for cross-scatter. A semi-anthropomorphic thorax phantom was used with increasing thicknesses of tissue-equivalent material to simulate small, medium, large and extra-large patients. Phantoms were scanned using single-source and dual-source protocols at 80, 100, 120 and 140 kV, and the mean and standard deviation of the CT numbers in a water-equivalent cylinder located centrally within the phantom measured. For this comparison, images reconstructed using only tube A data from the dual-source acquisition were compared to the single-source images, also obtained using tube A. The differences in the mean and standard deviation of the measured CT numbers between the dual-source tube A images, which were corrected for cross-scatter, and the single-source images, where no cross-scatter existed, were determined for all tube energies and phantom sizes. The differences in mean CT number ranged from -5.2 to 1.3 HU, and the differences in standard deviations ranged from -4.5 to 3.0 HU. We conclude, therefore, that use of the evaluated on-line cross-scatter correction algorithm results in negligible differences in CT number and image noise between single-source and dual-source image data, independent of phantom size and tube potential.

X-ray scatter correction is an open problem in the research of cone beam CT (CBCT). In this paper, using semitransparent beam stop array (BSA) introduced recently¹, an improved BSA method² is proposed. A simple iterative correction algorithm is developed based on the knowledge that mostly primary varies continuously. With the proposed method, scatter correction could be accomplished without extra scan. Experiments are carried out based on the Monte Carlo (MC) simulation (EGSnrc), the mean square error (MSE) is reduced from 50.71% (with no correction) to 2.54%, and there is no visible negative impact introduced by the correction.

We are investigating methods for computational scatter estimation for scatter correction in cone-beam computed tomography. We have developed an analytical method for estimating single scatter. The paper discusses our analytical method and its validation using Monte Carlo simulations. The paper extends previous results to include both Compton and Rayleigh single scatter interactions. The paper also discusses the potential for hybrid scatter estimation, in which empirical measurements of the total scatter signal in the collimator shadow may be used to augment computational single scatter estimates and thus account for multiple scatter.

The use of cone beam computed tomography (CBCT) is growing in the clinical arena, due to its ability to provide 3-D information during interventions, its high diagnostic quality (sub-millimeter resolution), and its short scanning times (10 seconds). In many situations, the reconstructions suffer from artifacts from high contrast objects (due mainly to angular sampling by the projections or by beam hardening) which can reduce image quality. In this study, we propose a novel algorithm to reduce these artifacts. In our approach, these objects are identified and then removed in the sinogram space by using computational geometry techniques. In particular, the object is identified in a reconstruction from a few views. Then, the rays (projection lines) intersecting the high contrast objects are identified using the technique of topological walk in a dual space which effectively models the problem as a visibility problem and provides a solution in optimal time and space complexity. As a result, the corrections can be performed in real time, independent of the projection image size. Subsequently, a full reconstruction is performed by leaving out the high contrast objects in the reconstructions. Evaluations were performed using simulations and animal studies. The artifacts are significantly reduced when using our approach. This optimal time and space complexity and relative simple implementation makes our approach attractive for artifact reduction.

The new Solid State X-ray Image Intensifier (SSXII) is being designed based on a modular imaging array of Electron Multiplying Charge Couple Devices (EMCCD). Each of the detector modules consists of a CsI(Tl) phosphor coupled to a fiber-optic plate, a fiber-optic taper (FOT), and an EMCCD sensor with its electronics. During the optical coupling and alignment of the modules into an array form, small orientation misalignments, such as rotation and translation of the EMCCD sensors, are expected. In addition, barrel distortion will result from the FOTs. Correction algorithms have been developed by our group for all the above artifacts. However, it is critical for the system's performance to correct these artifacts in real-time (30 fps). To achieve this, we will use two-dimensional Look-Up-Tables (LUT) (each for x and y coordinates), which map the corrected pixel locations to the acquired-image pixel locations. To evaluate the feasibility of this approach, this process is simulated making use of parallel coding techniques to allow real-time distortion corrections for up to sixteen modules when a standard quad processor is used. The results of this simulation confirm that tiled field-of-views (FOV) comparable with those of flat panel detectors can be generated in ~17 ms (>30 fps). The increased FOV enabled through correction of tiled images, combined with the EMCCD characteristics of low noise, negligible lag and high sensitivity, should make possible the practical use of the SSXII with substantial advantages over conventional clinical systems. (Support: NIH Grants R01EB008425, R01NS43924, R01EB002873)

Cone-beam CT (CBCT) is being increasingly used in modern radiation therapy. However, as compared to conventional CT, the degraded image quality of CBCT hampers its applications in radiation therapy. Due to the large volume of x-ray illumination, scatter is considered as one of the fundamental limitations of CBCT image quality. Many scatter correction algorithms have been proposed in the literature, while drawbacks still exist. In this work, we propose a correction algorithm which is particularly useful in radiation therapy. Since the same patient is scanned repetitively during one radiation treatment course, we measure the scatter distribution in one scan, and use the measured scatter distribution to estimate and correct scatter in the following scans. A partially blocked CBCT is used in the scatter measurement scan. The x-ray beam blocker has a strip pattern, such that the whole-field scatter distribution can be estimated from the detected signals in the shadow region and the patient rigid transformation can be determined from the reconstructed image using the illuminated detector projection data. From the derived patient transformation, the measured scatter is then modified accordingly and used for scatter correction in the following regular CBCT scans. The proposed method has been evaluated using Monte Carlo simulations and physical experiments on an anthropomorphic chest phantom. The results show a significant suppression of scatter artifacts using the proposed method. Using the reconstruction in a narrow collimator geometry as a reference, the comparison also shows that the proposed method reduces reconstruction error from 13.2% to 3.8%. The proposed method is attractive in applications where a high CBCT image quality is critical, for example, dose calculation in adaptive radiation therapy.

In dental treatments where metal is indispensable material and dental implants require precise structural measurements of teeth and bones, the ability of CT scanners to perform Metal Artifact Reduction (MAR) is a very important yet unsolved problem. The increasing need for dental implants is raising the demand for a conebeam CT. In this paper, an MAR method of the Metal Erasing Method (MEM) is extended to three dimensions. Assuming that metals are completely opaque to X-ray, MEM reconstructs metals and other materials separately, then combines them afterward. 3D-MEM is not only more efficient but performs better than the repetition of MEM, because it identifies metals more precisely by utilizing the continuity of metals in the third dimension. Another important contribution of the research is the application of advanced binarization techniques for identifying metal-corrupted areas on projection images. Differential histogram techniques are applied to find an adequate threshold value. Whereas MEM needs to identify metals on a sinogram that covers the all rotation angles with a single threshold value, identifying metals on each projection image with an individual value is an important benefit of 3D-MEM. The threshold value varies per projection angle, especially by the influence of the spine and scull, that are objects outside of the field of view. The performance of 3D-MEM is examined using a subject who has as many as 12 pieces of complex metals in his teeth. It is shown that the metals are successfully identified and the grade of metal artifact has been considerably reduced.

An X-ray computed tomography (CT) image including metallic objects suffers from annoying metal artifacts such as shades and streaks. In this paper, we propose a novel algorithm for reducing metal artifacts via a reprojectionreconstruction process. In the proposed algorithm, we first reconstruct a CT image from the original projection data. We then remove metallic object regions and replace them with the value of soft-tissue; apply total-variation-based smoothing to the image in order to reduce streak artifacts while preserving the shapes of non-metallic objects; and obtain the reprojection data of the smoothened image. Even though the reprojection data do not contain metallic objects, remaining shade artifacts (especially in the regions between metal objects) still affect the reprojection data. Those artifacts are found to be mainly concentrated in overlapping regions of metal-traces in the reprojection data. Hence, we horizontally interpolate the overlapping region with intensity values of its boundary pixels. We then replace whole metal trace regions in the original projection data with the processed reprojection data. The completed projection data are then used for the reconstruction of the final image. The proposed algorithm can reduce streak and shade artifacts while preserving the shape of non-metallic objects. It is proved that the proposed algorithm provides noticeably better performance in metal artifact reduction compared with the algorithms based on linear interpolation and the model image reprojection.

Refining the sampling geometry of a CT scanner is a standard approach used for reduction of aliasing artifacts in CT images. Although this leads to reduction of the artifacts, the principal problem of aliasing streaks artifacts remains unsolved. A different approach is proposed, which in some special cases can solve the problem very efficiently. It is shown that under certain specific conditions, the sum of images reconstructed from the data collected within different sampling geometries is free of aliasing. These conditions are studied and practical situations where they can be realized are discussed.

A new method for attenuation compensation (AC) in mesh-domain SPECT OSEM reconstruction using strip-area approximation (SAAC) is introduced and compared to single-ray AC (SRAC). SAAC uses the polygonal area of the intersection of a mesh element (ME) and a tube-of-response (TOR) for defining an effective length of photon transit and an effective attenuation coefficient. This approach to AC is compared to SRAC, which defines the effective length of photon transit as the intersection of a single ray and a ME and the effective attenuation coefficient as the mean along the ray path. Comparative quantitative and qualitative analysis demonstrated that SAAC outperformed SRAC in terms of reconstruction image accuracy and quality.

The upper limit of the amount of x-rays that are scattered from a SPECT/CT room and are acquired by an adjacent gamma camera is estimated using physical principles and approximations. Methods: We first estimated the amount of xrays scattered from the patient to the ceiling of the SPECT/CT room, then the amount scattered from the ceiling through the gap between the ceiling and the top of lead walls to reach outside of the room, and finally the amount acquired by an adjacent gamma camera into the Tl-201 data. Results: The counts of scattered x-ray photons acquired in the Tl-201 energy window can reach 0.12% of the CT primary counts when the standard 2.13 m high lead walls are used for the SPECT/CT room. Due to the high CT counts, contamination to the Tl-201 data cannot be ignored. It is not effective to reduce the contamination by increase the lead height or change the floor plan because the scattered x-rays reduce moderately with increasing lead height or different floor plans. When the lead height increases from 2.13 m to 2.74 m, for example, the amount of scattered x-rays only decreases by 20%. With the same 2.13 m lead height, there is little difference in the amount of scattered x-rays for three different floor plans. Conclusions: The standard lead walls for a SPECT/CT room cannot prevent scattered x-rays from severe contamination to the Tl-201 data acquired by an adjacent gamma camera. Since dramatic increase of lead height is costly and often prohibitive due to the heavy load, we recommend that Tl-201 studies be stopped when an adjacent CT scanner is in operation.

We investigated the potential use of CMOS (complementary metal-oxide-semiconductor) imaging detectors with a pixel pitch of 48 μm for mammography. Fundamental imaging characteristics were evaluated in terms of modulation-transfer function (MTF), noise-power spectrum (NPS), and detective quantum efficiency (DQE). The magnitudes of various image noise sources, such as optical photons, direct x rays unattenuated and scattered x rays from the scintillator, and additive electronic noise, were measured and analyzed. For the analysis of the measurement results, we applied a model describing the signal and noise transfer based on the cascaded linear-systems approach. The direct x-ray was very harmful to the detector noise performance with white noise characteristics in the spatial frequency domain, and which significantly degraded the spatial-frequency-dependent DQE at higher frequencies. Although the use of a fiber-optic plate (FOP) reduces the detector sensitivity and the MTF performance, it enhances the DQE performance by preventing the direct x-ray photons from the absorption within the photodiode array.

We study flat detectors for X-ray imaging performance degradation. In cone beam C-arm-CT, memory effects have a detrimental effect on image quality. Depending on the magnitude and history of irradiance differences, detector sensitivity variations may persist for a long period of time (days) and are visible as rings upon 3D reconstruction. A new method is proposed for reducing memory effects produced in CsI:Tl based Flat Detector X-ray imaging, which is based upon trap-filling by UV-light. For experiments, a commercial detector has been modified such that UV back-lighting is accomplished. A regular LED refresh light array for reducing photodiode temporal effects is interleaved with UV LED sub-arrays of different wavelengths in the near UV range. The array irradiates the scintillator through translucent parts of the detector substrate. In order to assess the efficacy of the method, ghost images are imprinted by well-defined transitions between direct radiation and attenuated or shuttered radiation. As an advantage, the new method accomplishes ghost-prevention, either by (1) continuous trap-filling at image-synchronous UV light pulsing, or (2) by applying a single dose of UV light. As a result, ring artefacts in reconstructed 3D-images are reduced to low levels. An effective wavelength has been found and an equilibrium UV dosage could be set for effective trap-filling. The overall sensitivity of the detector increases at saturated trap-filling. It was found that with optimised detector settings, i.e. optimum saturated trap-filling, the dependence on X-ray irradiation levels is low, so that the usage of the detector and its performance is robust.

A new pixel readout architecture is presented for amorphous selenium (a-Se) direct conversion radiation detectors. Photon-counting operation provides excellent sensitivity to low radiation doses but saturates the system at medium to high doses due to the poor charge transport properties of a-Se. Thus, we present an a-Se readout circuit design that is also capable of dynamically operating in integrating mode to enable the detection of high-dose radiation. This extends the resolvable dynamic range of the imaging system from very low gamma-ray count rates to very high flux x-ray radiations. The readout circuit is very promising for applications such as mammography tomosynthesis, and its benefits can also be extended to other radiation detectors. Finally, we present preliminary spectroscopy results with a-Se.

We fabricated an X-ray beam filter housing which can acquire large-area 2-dimensional images with a designated narrow band X-ray energy which was generated from the wide energy spectrum of the X-ray beam. The filter housing consists of an array of reflectors and each reflector filters the input X-ray energy from an ordinary X-ray tube and passes an X-ray beam of quasi-monochromatic energy. With a precise alignment of the whole reflectors in the filter housing device it is possible to make the total quasi-monochromatic X-ray beams cover a large area for imaging. The substrate of the reflector itself absorbs some of X-ray photons, which generates shadow of the layers on the image. In order to solve this problem the system was made to rotate around the focal spot of the X-ray tube during the X-ray image acquisition, which resembles the motion of a searchlight, hence there is no blind spot to the X-ray beam. At a preliminary stage we obtained images for a short exposure time of less than 1 second. Representative spectra and full field CDMAM phantom image of 197 mm × 238 mm acquired from the filter housing rotation method are presented. And the advantage of the monochromatic X-ray against the conventional polychromatic X-ray in terms of contrast is investigated.

Amorphous selenium (a-Se) is well known to provide superior spatial resolution and low dark current when used as a direct conversion X-ray photoconductor in flat panel detectors (FPD). However, a-Se properties are also known to fluctuate at higher environmental temperatures, so the temperature has to be carefully controlled. To overcome this problem we developed a newly modified a-Se photoconductor with electrical and X-ray characteristics that remain constant at temperatures up to 70 degrees C. On the other hand, in terms of a-Se dark current levels, the higher the electrical field, the higher the dark current level. For this reason, conventional a-Se photoconductors are used at a comparatively low electric field of 10 V/μm. We also investigated the electrical characteristics of film compositions containing a-Se that provide high gain and low dark current. Experiments were made with sandwich cells and then with CMOS (50 μm pixel pitch) readout panels. Our new a-Se photoconductor operated at 40 V/μm delivers sensitivity 3 to 4 times higher than the conventional a-Se operated at 10 V/μm, while keeping the dark current density at 5 pA/mm². This a-Se photoconductor will prove effective for low-dose X-ray imaging including mammography and tomosynthesis.

We exploit the development of a pixel-structured scintillator that would match the readout pixel array, such as a photodiode array. This combination may become an indirect-conversion detector having high x-ray sensitivity without sacrificing the inherent resolving power defined by the pixel geometry of the photodiodes, because the scintillation material has a relatively high atomic number and density compared with the photoconductors, and the pixel-structured design may provide a band-limited modulation-transfer function (MTF) characteristic even with a thicker scintillator. For the realization of pixel-structured scintillators, two-dimensional (2D) array of pixel-structured wells with a depth of 100μm was prepared by using a deep reactive ion etching (DRIE) process on a silicon wafer. Then, Gd₂O₂S:Tb phosphor powders with organic binders were filled within the well array by using a sedimentation method. Three different pixel designs of 50, 100 and 200 μm with a wall (or septum) thickness of 10 μm were considered. Each sample size was 20 × 30 mm² considering intra-oral imaging. The samples were coupled to the CMOS photodiode array with a pixel pitch of 48 μm and the imaging performances were evaluated in terms of MTF, NPS (noise-power spectrum) and DQE (detective quantum efficiency) at intra-oral imaging conditions. From the measurement results, the sensitivities of the samples with 50, 100 and 200 μm pitch designs were about 12, 25 and 41% of that of the reference commercial phosphor screen (MinR-2000). Hence the DQE performances at 0.2 lp/mm were about 3.7, 9.6, 22.7% of the reference screen. According to the Monte Carlo simulations, the lower sensitivity was due to the loss of optical photons in silicon walls. However, the MTF performance was mainly determined by the designed pixel apertures. If we make pixel-structured scintillators with a deeper depth and provide reflectance on walls, much enhanced DQE performance is expected.

It has been widely recognized that gain and offset corrections are essential for obtaining diagnostic image quality from flat-panel digital X-ray detectors. While such corrections are straightforward for detectors that are always powered and operate in a steady state, a new generation of battery-powered wireless detectors poses new challenges. Factors that need to be taken into account when optimizing the operation of such devices include image quality, battery life, robustness with respect to environmental variables and use patterns, and workflow, e.g., the readiness of the detector upon operator interaction, exposure lag, and image access time. Examples are given of the resolution to these problems for a new portable 35 × 43 cm² X-ray detector. Multiple power states are required to extend battery life, including a low power state that simply supports wireless communication while the detector is not taking images. As a consequence, the detector encounters slightly different operating conditions during the X-ray exposure compared with the dark images that are taken for offset compensation. A new offset-correction algorithm was developed to compensate for such systematic differences, and its performance was evaluated in terms of image uniformity and noise.

Autoradiography is a well established imaging modality in Biology and Medicine. This aims to measure the location and concentration of labelled molecules within thin tissue sections. The brain is the most anatomically complex organ and identification of neuroanatomical structures is still a challenge particularly when small animals are used for pre-clinical trials. High spatial resolution and high sensitivity are therefore necessary. This work shows the performance and ability of a prototype commercial system, based on a Charged-Couple Device (CCD), to accurately obtain detailed functional information in brain Autoradiography. The sample is placed in contact with the detector enabling direct detection of β- particles in silicon, and the system is run in a range of quasi-room temperatures (17-22 °C) under stable conditions by using a precision temperature controller. Direct detection of β- particles with low energy down to ~5 keV from ³[H] is possible using this room temperature approach. The CCD used in this work is an E2V CCD47-20 frame-transfer device which removes the image smear arising in conventional full-frame imaging devices. The temporal stability of the system has been analyzed by exposing a set of ¹⁴[C] calibrated microscales for different periods of time, and measuring the stability of the resultant sensitivity and background noise. The thermal performance of the system has also been analyzed in order to demonstrate its capability of working in other life science applications, where higher working temperatures are required. Once the performance of the system was studied, a set of experiments with biological samples, labelled with typical β- radioisotopes, such as ³[H], has been carried out to demonstrate its application in life sciences.

Active Matrix Flat Panel Imagers (AMFPIs) based on amorphous silicon (a-Si:H) thin film transistor (TFT) array is the most promising technology for large area biomedical x-ray imaging. a-Si:H TFT exhibits a metastable shift in its characteristics when subject to prolonged gate bias that results in a change in its threshold voltage (V_Τ) and a corresponding change in ON resistance (R_ON). If not properly accounted for, the V_Τ shift can be a major constraint in imaging applications as it contributes to the fixed pattern noise in the imager. In this work, we investigated the timedependent shift in V_Τ (ΔV_Τ) of a-Si:H TFTs stressed with the same bipolar pulsed bias used for static (chest radiography, mammography, and static protein crystallography) and real time imaging (low dose fluoroscopy at 15, 30 and 60 frames/second, and dynamic protein crystallography). We used the well known power law model of time dependent ΔVT to estimate the change in RON over time. Our calculation showed that RON can be decreased ~ 0.03 % per frame and ~ 5 % over 10,000 hours at 30 frames/second. We verified the theoretical results with measurement data. The implication of TFT metastability on the performance (NPS, and DQE) of biomedical imagers is discussed.

Stimulated by the introduction of clinical dual source CT, the interest in dual energy methods has been increasing in the past years. Whereas the potential of material decomposition by dual energy methods is known since the early 1980ies, the realization of dual energy methods is a wide field of today's research. Energy separation can be achieved with energy selective detectors or by varying X-ray source spectra. This paper focuses on dual energy techniques with varying X-ray spectra. These can be provided by dual source CT devices, operated with different kVp settings on each tube. Excellent spectral separation is the key property for use in clinical routine. The drawback of higher cost for two tubes and two detectors leads to an alternative realization, where a single source CT yields different spectra by fast kVp switching from reading to reading. This provides access to dual-energy methods in single source CT. However, this technique comes with some intrinsic limitations. The maximum X-ray flux is reduced in comparison to the dual source system. The kVp rise and fall time between each reading reduces the spectral separation. In comparison to dual source CT, for a constant number of projections per energy spectrum the temporal resolution is reduced; a reasonable trade of between reduced numbers of projection and limited temporal resolution has to be found. The overall dual energy performance is the guiding line for our investigations. We present simulations and measurements which benchmark both solutions in terms of spectral behavior, especially of spectral separation.

Dual energy x-ray CT images are computed using either image or projection data. The latter is thought to be preferable for two-material decomposition. Nonetheless, using effective energies of polychromatic x-ray beams at separated kVp values, material decomposition and pseudo-monochromatic reconstruction can be performed from reconstructed images. This image-based approach generates added noise which should benefit from applying processing for noise reduction. A set of material attenuation information so produced defines a vector space, which represents the true material property but is predefined from mass attenuation coefficients of major body-composite materials. We assumed 53keV and 72keV x-ray effective energies for 80kVp and 140kVp dual energy CT. The Gram-Schmidt process was applied to remove noise orthogonal to the vector spaces of the body-composite materials. Two-material decomposition was performed, and monochromatic and density images were reconstructed. Evaluations of image noise, Hounsfield unit accuracy, and resolution with a phantom, as well as with abdominal images, demonstrates improved CNR and SNR without loss of detail. This method of noise suppression also produced high quality density maps of two basis materials. Since dual energy CT currently uses slightly above average radiation dose, this method has the potential for lowering dose in addition to improving image quality.

Recently there has been significant interest in dual energy CT imaging with several acquisition methods being actively pursued. Here we investigate fast kVp switching where the kVp alternates between low and high kVp every view. Fast kVp switching enables fine temporal registration, helical and axial acquisitions, and full field of view. It also presents several processing challenges. The rise and fall of the kVp, which occurs during the view integration period, is not instantaneous and complicates the measurement of the effective spectrum for low and high kVp views. Further, if the detector digital acquisition system (DAS) and generator clocks are not fully synchronous, jitter is introduced in the kVp waveform relative to the view period. In this paper we develop a method for estimation of the resulting spectrum for low and high kVp views. The method utilizes static kVp acquisitions of air with a small bowtie filter as a basis set. A fast kVp acquisition of air with a small bowtie filter is performed and the effective kVp is estimated as a linear combination of the basis vectors. The effectiveness of this method is demonstrated through the reconstruction of a water phantom acquired with a fast kVp acquisition. The impact of jitter due to the generator and detector DAS clocks is explored via simulation. The error is measured relative to spectrum variation and material decomposition accuracy.

Dual-energy imaging with the injection of an iodinated contrast medium has the potential to depict cancers in the breast, by the demonstration of tumour angiogenesis and the suppression of the breast structure noise. The present study investigates the optimum monoenergetic beam parameters for this application. First, a theoretical study of the beam parameters was performed to find the best compromise between the quality of the dualenergy recombined image and the patient dose. The result of this analysis was then validated by phantom experiments using synchrotron monoenergetic radiation at the European Synchrotron Radiation Facility (ESRF, Grenoble, France). For an average breast of 5cm thickness and 50% glandularity, the theoretical simulations show an optimum at 20 keV for the low energy and 34 keV for the high energy, for a CsI detector of a standard mammography system. The SDNR variations with the low energy, the high energy or the dose repartition are very similar between the measurements on images acquired with synchrotron radiation and the simulated values. This ensures the accuracy of our theoretical optimization and the validity of the optimal beam parameters found in this study. The aim of this work is to demonstrate the potential of Dual-Energy CEDM (Contrast Enhanced Digital Mammography) with ideal monoenergetic sources, in order to provide an indicator of how to shape the polyenergetic spectra produced with classical X-ray sources for this application.

It is of clinical interest to quantify the concentration of materials in a three-component mixture with known chemical compositions, such as bone-mineral density (BMD) in a trabecular bone composed of calcium hydroxyappitite (CaHA), yellow- and red-marrow, and iron content in the liver composed of soft tissue, fat, and iron. Both pre- and postreconstruction dual-energy CT methods have been used to achieve this goal. The pre-reconstruction method is more accurate due to the elimination of beam-hardening artifacts. After obtaining the equivalent densities of the two basis materials, however, it is unclear how to accurately estimate the concentration of each material in the presence of the third material in the mixture. In this work, we present a pre-reconstruction three-material decomposition method in dualenergy CT to quantify the concentration of each material in a three-component mixture with known chemical compositions. This method employs a specific physical constraint on the equivalent densities of the two basis materials obtained from the conventional basis-material decomposition. We evaluated this method using simulation studies on two types of three-component mixtures: bone-water-fat and Iron-water-CaHA. The results demonstrated that an accurate estimation of the concentration for each material can be achieved with the proposed method.

This work aims at discriminating between soft and calcified coronary artery plaques using microCT with a multi-energywindow photon counting X-ray detector (PCXD). We have previously investigated a solid state X-ray detector which has the capability to count individual photons in different energy windows. The data from these energy windows may be treated as multiple simultaneous X-ray acquisitions within non-overlapping energy windows that can provide additional information about tissue differences. In this work, we simulated a photon counting detector with five energy windows. We investigated two approaches for using the energy information provided by this detector. First, we applied energy weighting to the reconstruction from different energy windows to improve the signal-to-noise ratio between calcified and soft plaques. This resulted in a significant improvement in the signal-to-noise ratio. Second, we applied the basis material decomposition method to discriminate coronary artery plaques based on their calcium content. The results were compared with those obtained using dual-kVp material decomposition. We observed significantly improved contrast-tonoise ratios for the PCXD-based approaches.

In "Spectral CT" based on energy-resolving photon-counting detectors (also "multi-energy CT") spectral information of transmitted X-radiation is measured in order to extract additional information about the material composition of the scanned object. Common practice is to decompose the attenuation line integrals into several components based on models of physical (e.g. photo/Compton/K-edge) or material properties (e.g. water/calcium). Scattered radiation causes a significant deterioration to the results, which are obtained with these models, as the measured spectrum in a specific detector element contains additional contributions which are not related to the attenuation in the respective line integral of the beam. In this paper the detrimental impact of scattered radiation in multi-energy CT is quantitatively analyzed by means of Monte-Carlo simulations. Large projection data sets of full rotational acquisitions are computed by combining noise-free analytical primary radiation with Monte-Carlo calculated scattered radiation of high statistical accuracy. The simulations show that, compared to the primary spectrum, the scatter spectrum is significantly shifted towards lower energies resulting in very high scatter-to-primary ratios for energies below 50keV. In the analysis of sinograms and reconstructed data using extended Alvarez-Macovsky decomposition into Photo-, Compton-, and K-edge images, it is revealed that scattered radiation causes significant inhomogeneity artifacts especially in the Photo image. Additionally "crosstalk" between Photo-, Compton- and K-edge images is found as K-edge structures appear in the other images and vice versa. Quantitatively it is found that due to scatter the reconstructed concentration of the K-edge material is up to 23 % smaller than its correct value.

Advances in the development of semiconductor based, photon-counting x-ray detectors stimulate research in the domain of energy-resolving pre-clinical and clinical computed tomography (CT). For counting detectors acquiring x-ray attenuation in at least three different energy windows, an extended basis component decomposition can be performed in which in addition to the conventional approach of Alvarez and Macovski a third basis component is introduced, e.g., a gadolinium based CT contrast material. After the decomposition of the measured projection data into the basis component projections, conventional filtered-backprojection reconstruction is performed to obtain the basis-component images. In recent work, this basis component decomposition was obtained by maximizing the likelihood-function of the measurements. This procedure is time consuming and often unstable for excessively noisy data or low intrinsic energy resolution of the detector. Therefore, alternative procedures are of interest. Here, we introduce a generalization of the idea of empirical dual-energy processing published by Stenner et al. to multi-energy, photon-counting CT raw data. Instead of working in the image-domain, we use prior spectral knowledge about the acquisition system (tube spectra, bin sensitivities) to parameterize the line-integrals of the basis component decomposition directly in the projection domain. We compare this empirical approach with the maximum-likelihood (ML) approach considering image noise and image bias (artifacts) and see that only moderate noise increase is to be expected for small bias in the empirical approach. Given the drastic reduction of pre-processing time, the empirical approach is considered a viable alternative to the ML approach.

The linearity between CT numbers and iodine concentrations is proved analytically provided the correlations between the atoms are negligible. This relationship is applied to correct the CT numbers in the ICA regions in monochromatic images of dual energy CT with the slow kV-switching technique where one scan with a low/high tube voltage follows by another scan with a high/low voltage. The iodine concentration may change significantly during the kV-switching. The resultant CT numbers in ICA regions may not be meaningful in the monochromatic images from pre-reconstruction decompositions because the data with the low/high voltages are not consistent. Using the linearity between CT numbers and iodine concentrations, the CT numbers in ICA regions can be corrected by referring to the CT numbers in the polychromatic images with the low/high voltages. A numerical simulation and a phantom study are performed to examine the linearity between CT numbers and iodine concentrations. The CT number correction by use of the linearity is tested in the numerical simulation study in slow kV-switching dual energy CT. The results show that the corrected CT numbers by use of the linearity are accurate.

X-ray scatter leads to erroneous calculations of dual-energy digital mammography (DEDM). The existing methods for scatter correction in DEDM are using anti-scatter grids or the pinhole-array interpolation method which is complicated and impractical. In this paper, a scatter correction algorithm for DEDM is developed based on the knowledge that scatter radiation in mammograms varies slowly and most pixels in mammograms are non-microcalcification pixels. The proposed algorithm only uses the information of low-energy (LE) and high-energy (HE) images. And it doesn't need anti-scatter grids, lead sheet and extra exposures. Our results show that the proposed scatter correction algorithm is effective. When using the simple least-squares fit and linear interpolation, the scatter to primary ratio (SPR) can be decreased from ~33.4% to ~2.8% for LE image and from ~26.2% to ~0.8% for HE image. Applying scatter correction to LE and HE images, the resultant background signal in the DE (dual-energy) calcification image can be reduced significantly.

The attenuation of x-rays in matter is dependent on the energy of the x-rays and the atomic composition of the matter. Attenuation measurements at multiple x-ray energies can be used to improve the identification of materials. We present a method to estimate the fractional composition of three materials in an object from x-ray CT measurements at two different energies. The energies can be collected from measurements from a single source-detector system at two points in time, or from a dual source-detector system at one point in time. This method sets up a linear system of equations from the measurements and finds the solution through a geometric construction of the inverse matrix equation. This method enables the estimation of the blood fraction within a region of living tissue in which blood containing an iodinated contrast agent is mixed with two other materials. We verified this method using x-ray CT simulations implemented in MATLAB, investigated the parameters needed to optimize the estimation, and then applied the method to a mouse model of lung cancer. A direct application of this method is the estimation of blood fraction in lung tumors in preclinical studies. This work was performed at the Duke Center for In Vivo Microscopy, an NCRR/NCI National Resource (P41 RR005959/U24 CA092656), and also supported by NCI R21 CA124584.

Recent publications in the field of Computed Tomography (CT) demonstrate the rising interest in applying dual-energy methods for material classification during clinical routine examinations. Based on today's standard of technology, dual-energy CT can be realized by either scanning with different X-ray spectra or by deployment of energy selective detector technologies. The list of so-called dual-kVp methods contains sequential scans, fast kVp-switching and dual-source CT. Examples of energy selective detectors are scintillator-based energyintegrating dual-layer devices or direct converter with quantum counting electronics. The general difference of the approaches lies in the shape of the effectively detected X-ray energy spectra and in the presence of crossscatter radiation in the case of dual-source devices. This leads to different material classification capabilities for the various techniques. In this work, we present detector response simulations of realistic CT scans with subsequent CT image reconstruction. Analysis of the image data allows direct and objective comparison of the dual-kVp, dual-layer, and quantum counting CT system concepts. The dual-energy performance is benchmarked in terms of image noise and Iodine-bone separation power at given image sharpness and dose exposure. For the case of dual-source devices the effect of cross-scatter radiation, as well as the benefit of additional filtering are taken into account.

Dual energy CT cardiac imaging is challenging due to cardiac motion and the resolution requirements of clinical applications. In this paper we investigate dual energy CT imaging via fast kVp switching acquisitions of a novel dynamic cardiac phantom. The described cardiac phantom is realistic in appearance with pneumatic motion control driven by an ECG waveform. In the reported experiments the phantom is driven off a 60 beats per minute simulated ECG waveform. The cardiac phantom is inserted into a phantom torso cavity. A fast kVp switching axial step and shoot acquisition is detailed. The axial scan time at each table position exceeds one heart cycle so as to enable retrospective gating. Gating is performed as a mechanism to mitigate the resolution impact of heart motion. Processing of fast kVp data is overviewed and the resulting kVp, material decomposed density, and monochromatic reconstructions are presented. Imaging results are described in the context of potential clinical cardiac applications.

We propose a method for material separation using dual energy data. Our method is suitable to separation of three or more materials. In this work we describe our method and show results of numerical simulation and with real dual-energy data of a head phantom. The proposed method of constructing the material separation map consists of the following steps: Data-domain dual energy decomposition - Vector plot - Density plot - Clustering - Color assignment. Density plots are introduced to allow automatic cluster separation. We use special image processing methods, including Gaussian decomposition, to improve the accuracy of material separation. We also propose using the HSL color model for better visualization and to bring a new dimension in material separation display. We study applications of bone removal and virtual contrast removal. Evaluation shows improved accuracy compared to standard methods.

In a conventional X-ray CT system, where an object is scanned with a selected incident x-ray spectrum, or kVp, the reconstructed images only approximate the linear X-ray attenuation coefficients of the imaged object at an effective energy of the incident X-ray beam. The errors are primarily the result of beam hardening due to the polychromatic nature of the X-ray spectrum. Modem clinical CT scanners can reduce this error by a process commonly referred to as spectral calibration. Spectral calibration linearizes the measured projection value to the thickness of water. However, beam hardening from bone and contrast agents can still induce shading and streaking artifacts and cause CT number inaccuracies in the image. In this paper, we present a dual kVp scanning method, where during the scan, the kVp is alternately switching between target low and high preset values, typically 80kVp and 140 kVp, with a period less than 1ms. The measured projection pairs are decomposed into the density integrals of two basis materials in projection space. The reconstructed density images are further processed to obtain monochromatic attenuation coefficients of the object at any desired energy. Energy levels yielding optimized monochromatic images are explored, and their analytical representations are derived.

The limitations of current CCD-based microCT X-ray imaging systems arise from two important factors. First, readout speeds are curtailed in order to minimize system read noise, which increases significantly with increasing readout rates. Second, the afterglow associated with commercial scintillator films can introduce image lag, leading to substantial artifacts in reconstructed images, especially when the detector is operated at several hundred frames/second (fps). For high speed imaging systems, high-speed readout electronics and fast scintillator films are required. This paper presents an approach to developing a high-speed CT detector based on a novel, back-thinned electron-multiplying CCD (EMCCD) coupled to various bright, high resolution, low afterglow films. The EMCCD camera, when operated in its binned mode, is capable of acquiring data at up to 300 fps with reduced imaging area. CsI:Tl,Eu and ZnSe:Te films, recently fabricated at RMD, apart from being bright, showed very good afterglow properties, favorable for high-speed imaging. Since ZnSe:Te films were brighter than CsI:Tl,Eu films, for preliminary experiments a ZnSe:Te film was coupled to an EMCCD camera at UC Davis Medical Center. A high-throughput tungsten anode X-ray generator was used, as the X-ray fluence from a mini- or micro-focus source would be insufficient to achieve high-speed imaging. A euthanized mouse held in a glass tube was rotated 360 degrees in less than 3 seconds, while radiographic images were recorded at various readout rates (up to 300 fps); images were reconstructed using a conventional Feldkamp cone-beam reconstruction algorithm. We have found that this system allows volumetric CT imaging of small animals in approximately two seconds at ~110 to 190 μm resolution, compared to several minutes at 160 μm resolution needed for the best current systems.

Current micro-CT scanners use either one or two x-ray tubes that are mechanically rotated around an object to collect the projection images for CT reconstruction. The rotating gantry design hinders the performance of the micro-CT scanner including the scanning speed. Based on the newly emerged carbon nanotube based distributed multi-beam x-ray array technology, we have proposed to build a stationary gantry-free multi-beam micro-CT (MBμCT) scanner. To investigate the feasibility of this concept, a prototype system using a source array with 20 individually controlled x-ray beams has been designed and tested. The prototype CT scanner can generate a scanning x-ray beam to image an object from different viewing angles (coverage of 36°) without any rotation. The electronics and software for system control and data have been implemented. The projected performance of the prototype MBμCT imaging system was discussed and some preliminary imaging results were presented.

The paper first highlights the use of multiple electronically controlled optical lenses, specifically, liquid lenses to realize an axial scanning confocal microscope with potentially less aberrations. Next, proposed is a signal processing method for realizing high resolution three dimensional (3-D) optical imaging using diffraction limited low resolution optical signals. Using axial shift-based signal processing via computer based computation algorithm, three sets of high resolution optical data is determined along the axial (or light beam propagation) direction using low resolution axial data. The three sets of low resolution data are generated by illuminating the 3-D object under observation along its three independent and orthogonal look directions (i.e., x, y, and z) or by physically rotating the object by 90 degrees and also flipping the object by 90 degrees. The three sets of high resolution axial data is combined using a unique mathematical function to interpolate a 3-D image of the test object that is of much higher resolution than the diffraction limited direct measurement 3-D resolution. Confocal microscopy or optical coherence tomography (OCT) are example methods to obtain the axial scan data sets. The proposed processing can be applied to any 3-D wave-based 3-D imager including ones using electromagnetic waves and sound (ultrasonic) waves. Initial computer simulations are described to test the robustness of the proposed high resolution signal processing method.

Recently, differential phase contrast computed tomography (DPC-CT) imaging methods have been successfully implemented using either synchrotron or x-ray tube generated x-rays. As far as image reconstruction is concerned, FBPtype reconstruction algorithms have been proposed. However, due to the intrinsic low photon efficiency of the system and the sampling requirement of the FBP reconstruction algorithms, the x-ray exposure time is unacceptably long, on the order of hours. In order to significantly shorten the data acquisition time, we proposed to acquire projection data at significantly fewer view angles. This poses a challenge in image reconstruction. In this work, we aimed at using the newly developed compressed sensing (CS) image reconstruction method to accurately reconstruct phase contrast CT images from vastly under-sampled data. Experimental data were utilized to validate our new reconstruction method. Our results demonstrate that the CS method enables acceptable image reconstruction in DPC-CT using significantly fewer view angles when compared with the FBP image reconstruction method.

At diagnostic X-ray energies, variations in the real component of the refractive index of tissues are several orders of magnitude larger than variations in the imaginary component, or equivalently, the X-ray attenuation coefficient. Consequently, X-ray phase-contrast imaging may permit the visualization of tissues that have identical, or very similar, X-ray absorption properties. Quantitative in-line phase-contrast tomography methods seek to reconstruct the three-dimensional (3D) complex X-ray refractive index distribution of tissue. Almost all existing image reconstruction algorithms for quantitative phase-contrast tomography make physical assumptions that are not consistent with benchtop or clinical implementations that employ an X-ray tube. Such assumptions include a monochromatic plane-wave X-ray beam that possesses perfect coherence properties. In this work, we implement and investigate a reconstruction theory for quantitative phase-contrast tomography that is suitable for use with polychromatic X-ray beams produced by a tube source. An image reconstruction algorithm is implemented that requires, as input data, two intensity measurements at each tomographic view that correspond to incident X-ray beams with distinct coherence properties. Computer-simulation studies that emulate polychromatic tube-based imaging conditions are conducted to assess the effectiveness of the reconstruction method for characterizing soft tissue structures.

Magnetoencephalography (MEG) is a multi-channel imaging technique. It measures the magnetic field produced by electric currents inside the brain via an array composed of a large number of superconducting quantum interference devices sensors. These measurements are then used to estimate the location and the strength of those electric currents. The estimated quantities are superimposed with anatomic magnetic resonance images via coregistration to create the magnetic source images. This paper attempts to present a theoretic framework of MEG beamforming for magnetic source imaging by aiming at some fundamental issues and providing several new findings in the five related aspects: (i) physical concept, (ii) mathematical formulation, (iii) statistical description, (iv) beamforming principle, and (v) magnetic source images.

The newly developed differential phase-contrast (DPC) imaging technique has attracted increasing interest among researchers. In a DPC system, the self-imaging effect and the phase-stepping method are implemented through three gratings to manifest phase contrast, and differentiated phase images can be obtained. An important advantage of this technique is that hospital-grade x-ray tubes can be used, allowing much higher x-ray output power and faster image processing than with micro-focus in-line phase-contrast imaging. A DPC-CT system can acquire images from different view angles along a circular orbit, and tomographic images can be reconstructed. However, the principle of DPC imaging requires multiple exposures to compute any differentiated phase image at each view angle, which raises concerns about radiation exposure via x-ray dose. Computer simulations are carried out to study the dose efficiency for DPC-CT for volume-of-interest breast imaging. A conceptual CBCT/DPC-CT hybrid imaging system and a numerical breast phantom are designed for this study. A FBP-type reconstruction algorithm is optimized for the VOI reconstruction. Factors including the x-ray flux and detector pixel size are considered and their effects on reconstruction image quality in terms of noise level and contrast-to-noise ratio are investigated. The results indicate that with a pixel size of 20 microns and a dose level of 5.7mGy, which is equivalent to the patient dose of a two-view mammography screening or a dedicated CBCT breast imaging scan, much better tissue contrast and spatial resolution can be achieved using the DPC-CT technique. It is very promising for possible application at pathology-level in vivo study for human breasts.

It has been proposed that the sensitivity of breast lesion detection can be improved with phase-contrast mammographic imaging. The recently introduced clinical system by Konica-Minolta, for example, reportedly yields enhanced lesion detectability. We hypothesize that the use of an optimized x-ray spectrum will result in even better performance. To test this hypothesis, we have performed a study of several clinical spectra from Mo and W sources over a broad spectral range. In the study, we have incorporated established dose measurements from a simple breast phantom used in the digital mammography literature, which has been updated to incorporate breast density properties in addition to conventional attenuation information. Established phase-contrast imaging simulation techniques, which employed a Fresnel propagator, were used to generate edge-enhanced radiographs for analysis. In addition, detector sensitivity and tube loading parameters were incorporated into the analysis. The resulting mammography images were analyzed via measurement of object edge-enhanced contrast.

In this study, we present phantom experiments and in-vivo human examination to evaluate the possibility of threedimensional (3D) photoacoustic imaging of the finger joints in a spherical scanning geometry. The phantom results show that 1mm thick "cartilage" can be accurately differentiated from the "bones" with a 1 MHz transducer. Results based on in-vivo finger joint study show that major anatomical features in the joint can be imaged, and the cartilages associated with the joint can be differentiated well from the phalanx. The results shown in this paper suggest that 3D PAT in a spherical scanning geometry has the potential to be used for early diagnosis of joint diseases

Frameworks for fixed partial denture made out of dental alloys thought classic techniques currently involve many errors like marginal and internal gaps. The aim of this study is to present alternative technologies in making frameworks from dental alloys using selective laser sintering/ selective laser melting (SLS/ SLM) and to investigate the marginal adaptation of the fixed dental prostheses using the en face optical coherence tomography. These procedures imply the use of a scanning device PROBIS, SMART OPTICS with the help of 3D Dental Scanner software. For digitizing the 3D model we used the Dental Wings Kunde Software. The files obtained were sent to a SLS/ SLM machine, Hint-Els rapidPro, where the CoCr powder was sintered/melt by selectively consolidating successive layers of powder material on top of each other, using thermal energy supplied by a focused and computer controlled laser beam. Through this technique can be produced up to 80 pieces in only one step. A parallel between the classic casting technique and this new technology reveal the least has several advantages: fast finishing time, excellent marginal and internal fit, biocompatibility and superior chemical properties. SLS/ SLM proved to be a promising technology that may overcome the classic ones, because of the superior marginal fit of the fixed dental prostheses to the teeth.

Magnetic particle imaging (MPI) based on the nonlinear interaction between internally administered magnetic nanoparticles and electromagnetic waves that externally irradiate the body has attracted attention for the early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signals are detected from the magnetic nanoparticles inside a target region. However, interference of the magnetization signals generated from the magnetic nanoparticles outside a target region due to nonlinear responses results in the degradation of image resolution. In this study, we clearly show that the degradation of image resolution is a result of the presence of even harmonics in the magnetization response of magnetic nanoparticles. We propose a new image reconstruction method for reducing these even harmonics and a correction method for suppressing the interference of the signals. This is achieved by taking into account the difference between the saturated waveform of the magnetization signal detected from the magnetic nanoparticles outside a target region and that detected from the magnetic nanoparticles inside a target region. In this study, we perform numerical analyses to prove that the image resolution in the molecular imaging technique can be improved by using our proposed image reconstruction method, which is based on the abovementioned ideas. Furthermore, a fundamental system is constructed and the numerical analyses are experimentally validated by using magnetic nanoparticles with a diameter of ~20 nm.

Investigating whether manganese transport is impaired in the optic nerve of small animal model is a new approach for evaluating optic neuritis. One needs to quantify signal intensity enhancement due to Mn2+ after intra-orbital injection, along the optic nerve from MR images. Quantification is very challenging as the optic nerve (ON) is not straight, its location does not correspond to standard slice orientation, the noise is substantial, and the signal is subject to inhomogeneity from the coil sensitivity. In this paper, we propose a semi-automatic method whereby 1) the retina point and the start of the chiasm in a mouse brain MR image are defined manually in a 3D visualization environment, 2) optic nerve in reformatted slices perpendicular to the optic nerve segment is semi-manually selected, 3) an automatic algorithm extracts the intensities along the optic nerve while correcting for intensity inhomogeneity, and 4) a model for the Mn2+ diffusion with a exponential decay function is fitted to the intensity profile. Results for the study of experimental autoimmune encephalomyelitis (EAE) are reported whereby statistically significant differences were found between the EAE and the control group.

Optical Coherence Tomography (OCT) allows a better characterization of dental prostheses. The detection of substance defects within the ceramic layers for metal-ceramic prostheses was demonstrated. The detected defects have a large volume and therefore there is a high likelihood for fracture lines to be generated in the proximal areas of the ceramic fixed partial dentures. If the detection of such defects is feasible before inserting the prosthesis into the oral cavity, then timely corrective measures are possible in order to avoid the fracture of the ceramic component later on. After noninvasive localization of cracks in ceramic fixed partial dentures, the effect of the biaxial loading on crack deflection/penetration at the ceramic interface was investigated. A biaxial loaded geometry was numerically investigated using Finite Element Analysis in order to determine the energy release rate. The obtained results could be used in conjunction with criteria at interface for estimating the path of the crack after the interface was reached.

1D array ultrasound subdicing is a common fabrication practice to avoid the presence of lateral modes near the center frequency of the transducer. The objective of this study is to theoretically analyze the effect of subdicing depth and width on the dispersion and resonance behavior of elastic guided wave propagation in 1D array transducers. The transducer is modeled as a periodic structure with the representative cell composed of one element. A semi-analytical finite-element (SAFE) method is derived to obtain the dispersion curves, group velocity and resonance mode shapes of a piezoelectric structure with arbitrary cross-section and periodic boundary conditions. Results indicate that resonant modes can occur at cutoff frequencies (wavenumber k = 0), where the phase velocity is infinite. Moreover, another interesting resonance behavior at zero-group-velocity (ZGV) points (wavenumber k ≠ 0) is observed where the phase velocity is finite. Theoretical results show that subdicing increases the number of waveguide modes, lowers the cut-off frequencies, increases the number of ZGV points and lowers the group velocities for flexural and extensional modes. Lower values of subdicing depth tend to increase the cut-off frequencies, but subdicing width has a minor effect on the dispersion curves. These important changes of the dispersion behavior are likely to influence the resonance characteristics and the bandwidth of the transducer. The analysis presented in this study provides a useful tool to optimize the design of 1D array ultrasound transducers and to gain better understanding of the complicated acoustic behavior of 1D array ultrasound transducers

Clear standards are lacking in the imaging modalities of the deficit in mild traumatic brain injury (MTBI) patients. The purpose of this study is to compare the image quality by signal distribution between 1.5 Tesla and 3 Tesla MRI in turbo spin echo (TSE) and gradient echo (GRE) images in normal hospital settings and to find preferences for which field to use in MTBI patients. We studied 40 MTBI patients with TSE and GRE; 20 patients were imaged at 1.5 T and 20 at 3 T. The imaging parameters were optimized separately for the two scanners. Histograms of the signal distribution in 22 ROIs were fitted to a 1-peak Gaussian model and the resulting peak positions were scaled in respect to the peak positions of genu of the corpus callosum and the caudate nuclei. Correlation of the contrast of the ROIs in reference to genu of the corpus callosum between both the two scanners and the two imaging sequences was good. Image contrast was similar at both in the TSE images; in the GRE images contrast improved from 1.5 T to 3 T. However, based on peak positions and widths, a slight drawback in the separability between the ROIs was observed when 1.5 T MRI was replaced by 3 T. No clear improvement in tissue contrast or separability of 3 T was found compared to 1.5 T. Imaging of MTBI with 3 T should therefore be based on other advantages of high-field imaging, such as improved SNR and spatial resolution.

Nowadays, optical tomographic techniques are of particular importance in the medical imaging field, because these techniques can provide non-invasive diagnostic images. The present study evaluates the potential of en-face optical coherence tomography (OCT) as a possible non-invasive high resolution imaging method in supplying the necessary information on the quality of dental hard tissues and defects of dental restorative materials. Teeth after several treatment methods are imaged in order to asses the material defects and micro-leakage of tooth-filling interface as well as to evaluate the quality of dental hard tissue. C-scan and B-scan OCT images as well as confocal images are acquired from a large range of samples. Cracks and voids in the dental structures as well as gaps between the dental interfaces and material defects are clearly exposed. The advantages of the OCT method consist in non-invasiveness and high resolution.

The longitudinal relaxation time, T₁, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T₁ maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T₁ from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T₁ estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

To increase the detection performance of breast cancers in mammograms, we need to improve shape delineation of micro calcifications and tumors. We accomplished this by developing a direct-conversion mammography system with an optical reading method and a new dual a-Se layer detector. The system achieved both small pixel size (50 micrometer) and a high Detective Quantum Efficiency (DQE) realized by 100 % of fill factor and noise reduction. We evaluated image quality performance and determined the best exposure conditions. We measured DQE and Modulation Transfer Function(MTF) according to the IEC62220-1-2. High DQE was maintained at a low radiation dosage, indicating that the optical reading method accompanies low noises. Response of MTF was maintained at up to the Nyquist frequency of 10 cyc/mm, which corresponds to 50 micrometer pixel size. To determine the best exposure conditions, we measured Contrast to Noise Ratio (CNR) and visually evaluated images of a resected breast under conditions of MoMo, MoRh, and WRh. There were occasional disagreements between the exposure conditions for achieving the maximum CNR and those for the best image graded by the visual evaluation. This was probably because CNR measurement does not measure effects of scattered X-ray. The images verified the improvement in detection and delineation performance of micro calcifications and tumors.

The purpose of this study was to quantitatively evaluate the effect of reducing radiation dose (i.e., mAs) on lesion detection in head CT examinations. We used a simulation package (Syngo Explorer) to reconstruct 5-mm thick CT images of the brain of one patient pertaining to the centrum semiovale, the basal ganglia, and the sella turcica. Lesion detection was measured using two Alternate Forced Choice (2-AFC) experiments that measure the lesion contrast (I92%) corresponding to a detection accuracy of 92%. Two observers performed experiments to investigate detection of low contrast lesions with four sizes ranging from 3 mm to 10 mm and at four x-ray beam intensities ranging from 105 mAs to 300 mAs. Results were plotted as log[I92%] versus log[mAs], and the slopes were measured for each lesion size. Lowering the mAs always reduced lesion detection performance in all images, and for all lesion sizes. Average slopes of the I92% versus mAs curves were -0.23 for 3 mm lesions, -0.16 for 4.5 mm lesions, and ~-0.11 for the 7 and 10 mm lesions. For the smallest lesions investigated (3 mm), doubling the x-ray intensity improved lesion detection performance by ~ 15%, whereas for the largest sized lesions (7 and 10 mm), doubling the tube current improved lesion detection performance by ~ 7%. The observed improvements in detection performance are markedly lower than predicted by the Rose model where a doubling of the tube current would be expected to improve detection performance by 29% at all lesion sizes.

X-ray equipment testing using phantoms that mimic the specific human anatomy, morphology, and structure is a very important step in the research, development, and routine quality assurance for such equipment. Although the NEMA XR21 phantom exists for cardiac applications, there is no such standard phantom for neuro-, peripheral and cardiovascular angiographic applications. We have extended the application of the NEMA XR21-2000 phantom to evaluate neurovascular x-ray imaging systems by structuring it to be head-equivalent; two aluminum plates shaped to fit into the NEMA phantom geometry were added to a 15 cm thick section. Also, to enable digital subtraction angiography (DSA) testing, two replaceable central plates with a hollow slot were made so that various angiographic sections could be inserted into the phantom. We tested the new modified phantom using a flat panel C-arm unit dedicated for endovascular image-guided interventions. All NEMA XR21-2000 standard test sections were used in evaluations with the new "headequivalent" phantom. DSA and DA are able to be tested using two standard removable blocks having simulated arteries of various thickness and iodine concentrations (AAPM Report 15). The new phantom modifications have the benefits of enabling use of the standard NEMA phantom for angiography in both neuro- and cardio-vascular applications, with the convenience of needing only one versatile phantom for multiple applications. Additional benefits compared to using multiple phantoms are increased portability and lower cost.

With the advancement of Computed Tomography technology, improving image quality while reducing patient dose has been a big technical challenge. The recent CT750 HD system from GE Healthcare provides significantly improved spatial resolution and the capability to reduce dose during routine clinical imaging. This paper evaluates the image quality of this system. Spatial resolution, dose reduction, noise, and low contrast detectability have been quantitatively characterized. Results show a quantifiable and visually discernable higher spatial resolution for both body and cardiac scanning modes without compromise of image noise. Further, equivalent image quality performance with up to 50% lower dose has been achieved.

Aim of this work was to identify proper figures of merit (FoM's) to quantitatively and objectively assess the whole acquisition process of a CT image and to evaluate which are more significant. Catphan® phantom images where acquired with a 64 slices computed tomography system, with head and abdomen protocols. Automatic exposure modulation system was on, with different settings. We defined three FoM's (Q, Q₁ and Q₂) including image quality parameters and acquisition modalities; two of them (Q and Q₁) include also a radiation dose quantity, the third (Q₂) does not. Then we drew from these the comparable FoM's (CNR, Q₁ *, Q₂), that do not have dose in their definitions, in order to investigate how they depend on perceived image quality. The FoM's were evaluated for each series. At the same time, expert observers evaluated the number of low contrast inserts seen in the phantom' images. The considered CNR, Q₁*, Q₂ FoM's are linearly related to the perceived image quality for both the acquisition protocols (head: r²=0.91;0.94;0.91; abdomen: r²=0.93;0.93;0.85). Q and Q₁ values analysis shows that these FoM's can distinguish between different acquisition modalities (head or abdomen) with statistically significant difference (p<0.05). The studied FoM's can be usefully used to quantitatively and objectively assess the whole CT image acquisition process. Those FoM's including also radiation dose (Q, Q₁) can be used to objectively quantify the equilibrium between image quality and radiation dose for a certain acquisition modality.

In order to optimize image quality, Figures of Merit (FOM) have been developed, including Signal-to-Noise ratio (SNR), Contrast-to-Noise ratio (CNR), and CNR²-to-Dose ratio (CNR²/PED). Some FOMs are designed to describe the performance of system components: Detective Quantum Efficiency (DQE) and Noise Equivalent Quanta (NEQ) are examples. A single FOM has the downside that optimization is inherently driven by the design of the FOM and cannot be changed. In this paper, we propose using a multi-parametric methodology for optimizing multiple input factors and multiple response measurements. This methodology has been developed in the statistical community as an offshoot of MANOVA (Multivariate ANalysis Of VAriance) analysis. In this paper, we acquired 120 images with various techniques and measured four individual image quality metrics. We then developed multivariate prediction formula for each metric and determined the global optimum operating point, using desirability functions. We demonstrate the power of this methodology over single FOM metrics.

The purpose of this study was to demonstrate CTDI estimation using GATE simulations, and to extend its techniques to various CT applications. We simulated various phantom sizes to estimate CTDI100 values for different patients. The simulations were performed using a single axial scan using standard PMMA (polymethylmethacrylate) head and body phantoms. Simulations of exposure in air were performed to compare simulated results with physically measured data. Simulations of absorbed dose in PMMA digital phantoms were performed to compare simulated results with physically measured data in corresponding PMMA physical phantoms at 5 different positions (at center, and 12hr, 3hr, 6hr, 9hr positions in phantoms). Additional simulations were performed for PMMA digital phantoms of various diameters (1-50 cm) at various kVp (80, 100, 120, 140 kVp) and mAs (100, 200, 300, 400 mAs) levels. For the PMMA head and body phantoms, the results of simulations showed an agreement with measured data by a maximum percent difference of 8.3% (head), 4.2% (body) for all energies applied. For the different positions, the results of simulations showed an agreement with measured data by a maximum per position difference of 4.7% (head), 5.1% (body) for 120 kVp. Within these limitations, for both various kVp and mAs levels, the results showed that CTDI100 values nonlinearly decreased as a function of diameter. For various diameters, the results showed that the CTDI100 values nonlinearly and linearly increased as a function of kVp and mAs, respectively.

The purpose of this study is to compare Contrast Detail Curves (CDCs) of unprocessed and processed digital images. Images of a CDMAM (contrast detail for mammography) phantom had been acquired at 29 kV Tungsten-Rhodium anode-filter combination and 100 mAs; unprocessed images were subsequently processed using five clinically available image processing algorithms. Scoring of CDMAM images was then performed using human observers and automatic reading. Five observers conducted a four-alternative forced-choice experiment on a set of four images, for each processing condition. For the automatic analysis of CDMAM images the CDCOM software program was used. Contrast Detail Curves were then computed both for the human and automatic reading by fitting a psychometric curve, after applying a smoothing algorithm (Gaussian filter). For both types of readings the CDCs from processed and unprocessed images were compared. We verified the statistical significance of the difference Δ between contrast threshold measurements at 0.1 mm target size (Figure of Merit, FoM), for unprocessed and processed images and for each image processing algorithm separately. The non-parametric bootstrap method was used. No statistical significant difference is found between raw and processed images. This study shows that CDMAM images may not be appropriate in assessing image processing algorithms.

Screen-film systems are used in mammography even now. Therefore, it is important to measure their physical properties such as modulation transfer function (MTF) or noise power spectrum (NPS). The MTF and NPS of screen-film systems are mostly measured by using a microdensitometer. However, since microdensitometers are not commonly used in general hospitals, it is difficult to carry out these measurements regularly. In the past, Ichikawa et al. have measured and evaluated the physical properties of medical liquid crystal displays by using a high-performance digital camera. By this method, the physical properties of screen-film systems can be measured easily without using a microdensitometer. Therefore, we have proposed a simple method for measuring the MTF and NPS of screen-film systems by using a high-performance digital camera. The proposed method is based on the edge method (for evaluating MTF) and the one-dimensional fast Fourier transform (FFT) method (for evaluating NPS), respectively. As a result, the MTF and NPS evaluated by using the high-performance digital camera approximately corresponded with those evaluated by using a microdensitometer. It is possible to substitute the calculation of MTF and NPS by using a high-performance digital camera for that by using a microdensitometer. Further, this method also simplifies the evaluation of the physical properties of screen-film systems.

The O-arm is a cone beam imaging system designed primarily to support orthopedic surgery and is also used for image-guided and vascular surgery. Using a gantry that can be opened or closed, the O-arm can function as a 2-dimensional (2D) fluoroscopy device or collect 3-dimensional (3D) volumetric imaging data like a CT system. Clinical applications of the O-arm in spine surgical procedures, assessment of pedicle screw position, and kyphoplasty procedures show that the O-arm 3D mode provides enhanced imaging information compared to radiographs or fluoroscopy alone. In this study, the image quality of an O-arm system was quantitatively evaluated. A 20 cm diameter CATPHAN 424 phantom was scanned using the pre-programmed head protocols: small/medium (120 kVp, 100 mAs), large (120 kVp, 128 mAs), and extra-large (120 kVp, 160 mAs) in 3D mode. High resolution reconstruction mode (512×512×0.83 mm) was used to reconstruct images for the analysis of low and high contrast resolution, and noise power spectrum. MTF was measured using the point spread function. The results show that the O-arm image is uniform but with a noise pattern which cannot be removed by simply increasing the mAs. The high contrast resolution of the O-arm system was approximately 9 lp/cm. The system has a 10% MTF at 0.45 mm. The low-contrast resolution cannot be decided due to the noise pattern. For surgery where locations of a structure are emphasized over a survey of all image details, the image quality of the O-arm is well accepted clinically.

The MTF (modulation transfer function) of digital radiography systems can be enhanced in the spatial frequency domain due to their high signal to noise ratio. A Wiener filter, which requires prior estimation of the noise and signal power spectrum of the images, was used to compensate MTF of the detector and thereby optimally restore the images details. We studied the noise characteristics of two flat panel detectors with structured columnar scintillator (CsI) and granular scintillator (Gd₂O₂S). A noise model formulating noise transfer process was applied to estimate the noise components for the filter. Signal model was based on dose of the application. We revisited the noise and signal model that was used in previous work by Souchay et al. for mammography application [1], considering the difference in detector characteristics and the applications (extremity x-ray) that we are specifically investigating. Starting with real clinical images, we used an observer study method to measure the visually optimal parameter for the Wiener filter. A set of clinical images was used to evaluate the radiologists' preferences to compensated images against the reference images. Statistical results from three experienced radiologists ranking results show that the compensated images are preferred over the reference images.

To improve quality of OSEM SPECT reconstruction in the mesh domain, we implemented an adaptive mesh generation method that produces tomographic mesh consisting of triangular elements with size and density commensurate with geometric detail of the objects. Node density and element size change smoothly as a function of distance from the edges and edge curvature without creation of 'bad' elements. Tomographic performance of mesh-based OSEM reconstruction is controlled by the tomographic mesh structure, i.e. node density distribution, which in turn is ruled by the number of key points on the boundaries. A greedy algorithm is used to influence the distribution of nodes on the boundaries. The relationship between tomographic mesh properties and OSEM reconstruction quality has been investigated. We conclude that by selecting adequate number of key points, one can produce a tomographic mesh with lowest number of nodes that is sufficient to provide desired quality of reconstructed images, appropriate for the imaging system properties.

Digital breast tomosynthesis (DBT) is a 3D imaging modality with limited angle projection data. The ability of tomosynthesis systems to accurately detect smaller microcalcifications is debatable. This is because of the higher noise in the projection data (lower average dose per projection), which is then propagated through the reconstructed image . Reconstruction methods that minimize the propagation of quantum noise have potential to improve microcalcification detectability using DBT. In this paper we show that penalized maximum likelihood (PML) reconstruction in DBT yields images with an improved resolution/noise tradeoff as compared to conventional filtered backprojection (FBP). Signal to noise ratio (SNR) using PML was observed to be higher than that obtained using the standard FBP algorithm. Our results indicate that for microcalcifications, using the PML algorithm, reconstructions obtained with a mean glandular dose (MGD) of 1.5 mGy yielded better SNR than that those obtained with FBP using a 4mGy total dose. Thus perhaps total dose could be reduced to one-third or lower with same microcalcification detectability, if PML reconstruction is used instead of FBP. Visibility of low contrast masses with various contrast levels were studied using a contrast-detail phantom in a breast shape structure with an average breast density. Images generated using various dose levels indicate that visibility of low contrast masses generated using PML reconstructions are significantly better than those generated using FBP. SNR measurements in the low-contrast study did not appear to correlate with the visual subjective analysis of the reconstruction indicating that SNR is not a good figure of merit to be used.

Currently available spiral/helical computed tomography (HCT) technologies have demonstrated the potential for CTbased virtual colonoscopy or CT-colonography (CTC). However, a major limitation for this clinical application is associated with the risk of high radiation exposure, especially for its use for screening purpose at a large population. In this work, we presented an improved Karhunen-Loeve (KL) domain penalized weighted least-squares (PWLS) strategy which considers the data correlation among the nearby angular views and nearby axial slices simultaneously so that a fully three-dimensional (3D) restoration problem can be reduced to a 1D operation and therefore an analytical calculation is feasible for highest computing efficiency. The KL-PWLS strategy was implemented and tested on computer simulated sinograms which mimic low-dose CT scans at different noise levels characterized by 50, 40, 30, 20 and 10 mAs respectively. The reconstructed images by the presented strategy demonstrated the potential of ultra low-dose CT at as low as 10 mAs for VC application. Further evaluation by receiver operating characteristic study is needed and is under progress.

We present a method for spatio-temporal filtration of dynamic CT data, to increase the signal-to-noise ratio (SNR) of image data at the same time maintaining image quality, in particular spatial and temporal sharpness of the images. Alternatively, the radiation dose applied to the patient can be reduced at the same time maintaining the noise level and the image sharpness. In contrast to classical methods, which generally operate on the three spatial dimensions of image data, noise statistics is improved by extending the filtration to the temporal dimension. Our approach is based on nonlinear and anisotropic diffusion filters, which are based on a model of heat diffusion adapted to medical CT data. Bilateral filters are a special class of diffusion filters, which do not need iteration to reach a convergence image, but represent the fixed point of a dedicated diffusion filter. Spatio-temporal, anisotropic bilateral filters are developed and applied to dynamic CT image data. The potential was evaluated using data from perfusion CT and cardiac dual source CT (DSCT) data, respectively. It was shown, that in perfusion CT, SNR can be improved by a factor of 4 at the same radiation dose. On basis of clinical data it was shown, that alternatively the radiation dose to the patient can be reduced by a factor of at least 2. A more accurate evaluation of the perfusion parameters blood flow, blood volume and time-to-peak is supported. In DSCT noise statistics can be improved using more projection data than needed for image reconstruction, however, as a consequence the temporal resolution is significantly impaired. Due to the anisotropy of the spatio-temporal bilateral filter temporal contrast edges between adjacent time samples are preserved, at the same time substantially smoothing image data in homogeneous regions. Also temporal contrast edges are preserved, maintaining the very high temporal resolution of DSCT acquisitions (~ 80 ms). CT examinations of the heart require careful dose management to reduce the radiation dose burden to the patient. The use of spatio-temporal diffusion filters allows for dose reduction at the same noise level, at the same time preserving spatial and temporal image resolution. Our approach can be extended to any imaging method, that is based on dynamic data, as an efficient tool for edge-preserving noise reduction.

This paper presents a fast cone beam reconstruction method accelerated on the graphics processing unit (GPU). We implement the Feldkamp, Davis, and Kress (FDK) algorithm on the OpenGL graphics pipeline, which allows us to exploit the full resources and capabilities available on the GPU. The proposed method differs from previous GPU-based methods in having an RGBA packing scheme capable of directly dealing with projections without rebinning. It also reduces the amount of computation by using a data reuse scheme, which is useful to save the memory bandwidth for this memory-intensive problem. Both schemes contribute to reduce the number of rendering passes, namely the number of kernel invocations on the GPU, realizing fast cone beam reconstruction. We show some experimental results obtained on a desktop PC with an nVIDIA GeForce 8800 GTX card. As a result, the proposed method takes 8.1 seconds to reconstruct a 512³-voxel volume from 360 512²-pixel projection images. This execution time is equivalent to a 15.6-fold speedup over a CPU implementation, showing 10% higher performance as compared with a previous OpenGL-based method that requires the single-slice rebinning of projections for acceleration. With respect to non-rebinned data, our method provides approximately three times higher performance than the previous method.

As a new three-dimensional breast imaging technique, breast tomosynthesis allows the reconstruction of an arbitrary set of planes in the breast from a limited-angle series of x-ray projection images. The breast tomosynthesis technique has been demonstrated as promising to improve early breast cancer detection. This paper represents a preliminary phantom study and computer simulation results of different breast tomosynthesis reconstruction algorithms with a novel carbon nanotube based multi-beam x-ray source. Five representative tomosynthesis reconstruction algorithms, including back projection (BP), filtered back projection (FBP), matrix inversion tomosynthesis (MITS), maximum likelihood expectation maximization (MLEM), and simultaneous algebraic reconstruction technique (SART) were investigated. Tomosynthesis projection images of a phantom were acquired with the stationary multi-beam x-ray tomosynthesis system. Reconstruction results from different algorithms were studied. A computer simulation study was further done to investigate the sharpness of reconstructed in-plane structures and to see how effective each algorithm is at removing out-of-plane blur with parallel-imaging geometries. Datasets with 9 and 25 projection images of a defined 3D spherical object were simulated with a total view angle of 50 degrees. Results showed that the multi-beam x-ray system is capable to generate 3D tomosynthesis images with faster speed compared with current commercial prototype systems. With simulated parallel-imaging geometry, MITS and FBP showed edge enhancement in-plane performance. BP, FBP and MLEM performed better at out-of-plane structure removal with larger number of projection images.

Digital tomosynthesis (DTS) often suffers from slow reconstruction speed due to the high complexity of the computation, particularly when iterative methods are employed. To fulfill clinical performance constraints, graphics cards (GPUs) were investigated and proved to be an efficient platform for accelerating tomographic reconstruction. However, hardware programming constraints often led to complicated memory management and resulted in reduced accuracy or compromised performance. In this paper we proposed a new GPU-based reconstruction framework targeting on tomosynthesis applications. Our framework benefits from latest GPU functionalities and improves the design from previous applications. A high-quality ray-driven forward projection help simplify the data flow when arbitrary acquisition matrices are provided. Our results show that a near-interactive reconstruction speed is achieved with the new framework at no loss of accuracy.

We demonstrate an improvement to cone-beam tomographic imaging by using a prior anatomical model. A protocol for scanning and reconstruction has been designed and implemented for a conventional mobile C-arm: a 9 inch image-intensifier OEC-9600. Due to the narrow field of view (FOV), the reconstructed image contains strong truncation artifacts. We propose to improve the reconstructed images by fusing the observed x-ray data with computed projections of a prior 3D anatomical model, derived from a subject-specific CT or from a statistical database (atlas), and co-registered (3D/2D) to the x-rays. The prior model contains a description of geometry and radiodensity as a tetrahedral mesh shape and density polynomials, respectively. A CT-based model can be created by segmentation, meshing and polynomial fitting of the object's CT study. The statistical atlas is created through principal component analysis (PCA) of a collection of mesh instances deformably-registered (3D/3D) to patient datasets. The 3D/2D registration method optimizes a pixel-based similarity score (mutual information) between the observed x-rays and the prior. The transformation involves translation, rotation and shape deformation based on the atlas. After registration, the image intensities of observed and prior projections are matched and adjusted, and the two information sources are blended as inputs to a reconstruction algorithm. We demonstrate recostruction results of three cadaveric specimens, and the effect of fusing prior data to compensate for truncation. Further uses of hybrid reconstruction, such as compensation for the scan's limited arc length, are suggested for future research.

In order to improve reconstructed image quality, we investigated performance of OSEM mesh-domain SPECT reconstruction with explicit prior anatomical and physiological information that was used to perform accurate attenuation compensation. It was accomplished in the following steps: (i) Obtain anatomical and physiological atlas of desired region of interest; (ii) Generate mesh that encodes properties of the atlas; (iii) Perform initial pixel-based reconstruction on projection dataset; (iv) Register the expected emission atlas to the initial pixel-based reconstruction and apply resulting transformation to meshed atlas; (v) Perform reconstruction in mesh-domain using deformed mesh of the atlas. This approach was tested on synthetic SPECT noise-free and noisy data. Comparative quantitative analysis demonstrated that this method outperformed pixel-based OSEM with uniform AC and is a promising approach that might lead to improved SPECT reconstruction quality.

A new type of X-ray CT scanning geometry is proposed. The geometry of the scanner includes a half ring detector array and resembles the geometry of a scanner of the fourth generation. Unlike the latter, the proposed system collects parallel projections allowing efficient collimation of the incident beam for the purpose of scatter reduction. The geometry of the data collected with the proposed scanner is ideal for algorithms developed for image reconstruction from parallel projections with a non-uniform sampling such as the Orthogonal Polynomial Expansion on Disk (OPED) algorithm. This scanner can be efficiently used in applications where high precision measurements at micrometer scales are required, e.g. in the exact quantification of the morphology of small animals.

SPECT is one of the nuclear medicine imaging techniques and widely used in the clinical applications. Different from CT, SPECT achieved the functional image of the organ of interest, and the diseases can be found much earlier. Conebeam SPECT reconstruction can improve the photon density and spatial resolution of the reconstructed image, but it is time consuming. In clinic, doctors usually just care about the region of interest (ROI), such as heart, not whole body. Local reconstruction can reduce the reconstruction time. In this paper, based on Novikov's analytical SPECT reconstruction algorithm, we built a framework for local cone-beam SPECT reconstruction with non-uniform attenuation. The simulation results show our reconstruction framework is feasible.

OPED is a reconstruction algorithm for Radon data based on orthogonal polynomial expansion on the disk. The algorithm involves a sum of N terms, which is determined by the number of view angles in the data. Evaluating on a rectangular grid of M×M pixels, the algorithm can be implemented with roughly O(N³) evaluations, if we assume M ≈ N, and the constant is rather large. The new implementation uses a particular polar grid, so that the evaluation operation is reduced to 2N³ + O(N² logN), a reduction of the evaluation time by a factor of more than 20 times. Linear interpolation on triangle is used to reduce our particular polar grid to the rectangular grid. Numerical experiments are presented to demonstrate the results.

MRI applications often require high spatial and/or temporal resolution within a region of interest (ROI) such as for perfusion studies. In theory, both spatial resolution and temporal resolution can be significantly improved using a ROI-focused MRI data acquisition scheme. However, in radial MRI, there is no such acquisition-based solution available. Traditional reconstruction methods to image the ROI by reducing the field of view produce aliasing artifacts when the dataset becomes truncated. Here we propose an interior MRI methodology to perform ROI reconstruction without artifacts. Methods: In contrast to the conventional wisdom that the interior problem does not have a unique solution, interior tomography has been recently proposed as an exact and stable solution to this longstanding problem. In this project, a ROI-focused radial MRI data acquisition scheme was developed, aided by a dedicated digital filter. We implemented this method in a 4T 90 cm bore Oxford magnet with a GE phantom and a transceiver TEM head coil. The parameters were 4 gauss/cm sonata gradients, 5 mm slice thickness, TE=30 ms, TR=200 ms, FOVs of 40 cm and 12 cm respectively. Results: Both numerical simulation and phantom experiments have demonstrated that the proposed interior MRI method can exactly reconstruct a ROI with increased spatial resolution (~4 fold) while keeping the same temporal resolution. The image artifacts from truncated projections are effectively eliminated. No crosstalk with the outside ROI region is involved using the proposed method. Conclusions: Our interior radial MRI method can be used for zoomed-in and fast

We have investigated the optical properties of Gd₂O₂S:Tb granular phosphor screens for the use in indirect-conversion detectors by using the Monte Carlo method. For the optical model of the phosphor screen, it was regarded as a weak absorbing medium in which scattering is caused by refraction at boundaries between the phosphor grains and organic binders. For the estimation of the light collection efficiency, we included thin passivation (e.g. SiO₂) and Si layers as a photodiode in the Monte Carlo geometry only because the optical photons which escape from the phosphor screen exit and towards the Si layer can contribute to signals. In addition, optical coupling materials (e.g., optical fluids), which are practically used in the indirect-conversion detector, were considered. In the Monte Carlo simulations, various design parameters of the phosphor screen were considered such as the refractive index of an optical coupler and passivation layer, a reflection coefficient at the screen backing, and the thickness of an optical coupler. According to the simulation results, the optical coupler played a great role both in light collection efficiency and point-spread function (PSF). The maximum light collection efficiency was achieved when the refractive index of the optical coupler matched to either that of the phosphor screen or that of the photodiode. Moreover, the matched refractive index provided a lesser light spread in the resulting images. The simulation method and result can provide guidelines for a better design of indirect-conversion detectors based on a photodiode array coupled to a phosphor screen.

This paper presents a statistical reconstruction algorithm for dual-energy (DE) CT of polychromatic x-ray source. Each pixel in the imaged object is assumed to be composed of two basis materials (i.e., bone and soft tissue) and a penalizedlikelihood objective function is developed to determine the densities of the two basis materials. Two penalty terms are used respectively to penalize the bone density difference and the soft tissue density difference in neighboring pixels. A gradient ascent algorithm for monochromatic objective function is modified to maximize the polychromatic penalizedlikelihood objective function using the convexity technique. In order to reduce computation consumption, the denominator of the update step is pre-calculated with reasonable approximation replacements. Ordered-subsets method is applied to speed up the iteration. Computer simulation is implemented to evaluate the penalized-likelihood algorithm. The results indicate that this statistical method yields the best quality image among the tested methods and has a good noise property even in a lower photon count.

Computed tomography (CT) has been extensively studied and widely used for a variety of medical applications. The reconstruction of 3D images from a projection series is an important aspect of the modality. Reconstruction by filtered backprojection (FBP) is used by most manufacturers because of speed, ease of implementation, and relatively few parameters. Iterative reconstruction methods have a significant potential to provide superior performance with incomplete or noisy data, or with less than ideal geometries, such as cone-beam systems. However, iterative methods have a high computational cost, and regularization is usually required to reduce the effects of noise. The simultaneous algebraic reconstruction technique (SART) is studied in this paper, where the Feldkamp method (FDK) for filtered back projection is used as an initialization for iterative SART. Additionally, graphics hardware is utilized to increase the speed of SART implementation. Nvidia processors and compute unified device architecture (CUDA) form the platform for GPU computation. Total variation (TV) minimization is applied for the regularization of SART results. Preliminary results of SART on 3-D Shepp-Logan phantom using using TV regularization and GPU computation are presented in this paper. Potential improvements of the proposed framework are also discussed.

In current dedicated breast computed tomography (mammotomography) systems, comfortable patient positioning on a stationary bed restricts the practicable range of source-detector trajectories, thus compromising the system's ability to adequately image the patient's anterior chest wall. This study examines the effect on detecting small, low-contrast lesion-like-spheres using limited angle x-ray source-detector trajectories and trajectories that intentionally raise the tomographic imaging system mid-acquisition. These modified acquisition paths may increase chest wall visualization, simplify the design of the imaging system and increase patient comfort by allowing the design of an improved patient bed. Thin walled balloons of various volumes filled with iodine act as surrogate high contrast lesions to initially investigate the effect of these novel trajectories. Then, stacks of 5mm acrylic spheres regularly spaced in concentric circles are placed in water to simulate a low contrast environment in a uniform scatter medium. 360° azimuthal scans are acquired at various bed heights with contiguous projections subsequently removed to create limited angle acquisitions from 240-360°. Projections from the different bed heights are interwoven to form trajectories that mimic discontinuously raising the imaging system mid-acquisition. The resulting iteratively reconstructed volumes are evaluated with an observer study. Initial images suggest that using limited angles and raising the system is possible while increasing the observer's ability to visualize objects near the chest wall. Based on the results of this study, an improved patient bed to facilitate chest wall imaging will be designed, and the feasibility of vertical system motion to increase imaged breast volume explored.

Conventional mammographic image contrast is derived from x-ray absorption, resulting in breast structure visualization due to density gradients that attenuate radiation without distinction between transmitted and scattered or refracted x-rays. This leads to image blurring and contrast reduction, hindering the early detection of small or otherwise occult cancers. Diffraction enhanced imaging (DEI) allows for dramatically increased contrast with decreased radiation dose compared to conventional mammographic imaging due to monochromatic x-rays, its unique refraction-based contrast mechanism and excellent scatter rejection. However, a lingering drawback to the clinical translation of DEI has been the requirement for synchrotron radiation. Our laboratory developed a DEI prototype (DEI-PR) utilizing a readily available Tungsten xray tube source and traditional DEI crystal optics, providing soft tissue images at 60keV. To demonstrate the clinical utility of our DEI-PR, we acquired images of full-thickness human breast tissue specimens on synchrotron-based DEI, DEI-PR and digital mammography systems. A reader study was designed to allow unbiased assessment of system performance when analyzing three systems with dissimilar imaging parameters and requiring analysis of images unfamiliar to radiologists. A panel of expert radiologists evaluated lesion feature visibility and histopathology correlation after receiving training on the interpretation of refraction contrast mammographic images. Preliminary data analysis suggests that our DEI system performed roughly equivalently with the traditional DEI system, demonstrating a significant step toward clinical translation of this modality for breast cancer applications.

Obese patients present challenges in obtaining sufficient x-ray exposure over reasonable time periods for acceptable CT image quality. To overcome this limitation, the exposure can be divided between two x-ray sources using a dualsource (DS) CT system. However, cross-scatter issues in DS CT may also compromise image quality. We evaluated a DS CT system optimized for imaging obese patients, comparing the CT number accuracy and uniformity to the same images obtained with a single-source (SS) acquisition. The imaging modes were compared using both solid cylindrical PMMA phantoms and a semi-anthropomorphic thorax phantom fitted with extension rings to simulate different size patients. Clinical protocols were used and CTDIvol and kVp were held constant between SS and DS modes. Results demonstrated good agreement in CT number between SS and DS modes in CT number, with the DS mode showing better axial uniformity for the largest phantoms.

The purpose of the work was to test if effective detective quantum efficiency (eDQE) could be useful for optimisation of radiographic factors for computed radiography (CR) for adult chest examinations. The eDQE was therefore measured across a range of kilovoltage, with and without an anti-scatter grid. The modulation transfer function, noise power spectra, transmission factor and scatter fraction were measured with a phantom made of sheets of Aluminum and Acrylic. The entrance air kerma was selected to give an effective dose of 4.9 μSv. The effective noise equivalent quanta (eNEQ) is introduced in this work. eNEQ can be considered equal to the number of X-ray quanta equivalent in the image corrected for the amount of scatter and the blurring processes. The eNEQ was then normalised to account for slight differences in the effective dose (eNEQ_ED). The peak eNEQ_ED was largest at 80 kV and 100 kV with no grid and with grid respectively. At each kilovoltage, the eNEQ_ED and eDQE were between 10% and 70% larger when the grid was not used. The results show that 80 kV without grid is the most suitable exposure conditions for CR in chest. This is consistent with clinical practice in the UK and previous publications recommending a low kV technique for CR for average sized adult chest imaging.

We developed a digital radiography (DR) system using a new amorphous selenium (a-Se) based direct-detection flatpanel detector which has a pixel pitch of 0.168mm, a fill factor of 83%, and a total active imaging area is 17"×17". Our new system consists of an X-ray generator, two flat-panel detectors, an X-ray tube, a bucky stand, a bucky table, a control box, an image processing unit and another component. The performance of this imaging system has been measured and compared with that of our previous system used an a-Se based flat-panel detector, however, which has a pixel pitch of 0.139mm, a fill factor of 82% and a total active imaging area of 14"×17". In order to evaluate the system performance quantitatively, the modulation transfer function (MTF), detective quantum efficiency (DQE) and noise power spectrum (NPS) were measured. At 3.0 lp./mm, the measured MTF was 56%, and DQE were 25% approximately for a new flat-panel detector. In case of the previously used flat-panel detector, the MTF and DQE at 3.0 lp./mm were 75% and 12%, respectively. The MTF of a new flat-panel detector was lower than that of a previous detector, however DQE of a new detector was higher than that of a previous detector at whole spatial frequency region. In conclusion, our new DR system is capable of providing good image quality in aspect of the physical characteristics although the MTF is relatively lower than previously developed system.

In this paper we report the development of a high resolution dynamic micro-computed tomography (CT) scanner with a stationary mouse bed using a compact carbon nanotube (CNT) x-ray tube. The scanner comprises a rotating x-ray tube and detector pair and a stationary and a horizontally positioned small animal bed. The system is optimized for in vivo mouse cardiac imaging. Its performance is evaluated with CT scans of phantoms and free-breathing mice. The modulation transfer function (MTF) at 10% is 5 lp/mm. At single frame acquisition, mouse cardiac micro-CT at 20msec temporal resolution has been demonstrated by prospectively gating the imaging acquisitions to both respiration and cardiac signals.

The sampling geometry of CT-scanners plays an important role in the reconstruction of images. We have previously reported a test-device that directly collects the Radon data within a special scanning geometry, whose acquired data can be efficiently treated with series expansion algorithms such as, for example, OPED (Orthogonal Polynomial Expansion on Disc). This geometry has the potential of reducing the radiation exposure of the patient by about a factor of two. However, a fourth of the data must be obtained by interpolation within the measured projections. In this contribution, we show by a Monte Carlo simulation that this interpolation has no significant influence on the quality of the reconstructions.

Computed radiography (CR) is considered a drop-in addition or replacement for traditional screen-film (SF) systems in digital mammography. Unlike other technologies, CR has the advantage of being compatible with existing mammography units. One of the challenges, however, is to properly configure the automatic exposure control (AEC) on existing mammography units for CR use. Unlike analogue systems, the capture and display of digital CR images is decoupled. The function of AEC is changed from ensuring proper and consistent optical density of the captured image on film to balancing image quality with patient dose needed for CR. One of the preferences when acquiring CR images under AEC is to use the same patient dose as SF systems. The challenge is whether the existing AEC design and calibration process-most of them proprietary from the X-ray systems manufacturers and tailored specifically for SF response properties-can be adapted for CR cassettes, in order to compensate for their response and attenuation differences. This paper describes the methods for configuring the AEC of three different mammography units models to match the patient dose used for CR with those that are used for a KODAK MIN-R 2000 SF System. Based on phantom test results, these methods provide the dose level under AEC for the CR systems to match with the dose of SF systems. These methods can be used in clinical environments that require the acquisition of CR images under AEC at the same dose levels as those used for SF systems.

In recent years, there has been an increasing number of integration for using the micro CT scanners, either home-built bench-top or commercially made, as the small animal radiation therapy irradiator in several research groups. In this paper, we study the x-ray beam physics such as the percentage depth dose distribution and their dose conformity characteristics using Monte Carlo simulation method for a series of photon energy levels often found in the current commercial micro CT imaging systems. Micro CT scanners have been one of the key imaging modalities in the current state-of-the-art molecular imaging techniques and their applications in various biomedical research areas have been increasing tremendously in recent years due to the ultra-high image quality. Tumor growth development and the corresponding therapeutic response in the small animal model study can be evaluated by a micro CT imaging system. In the most current advanced commercially available micro CT units, the nominal spatial resolution is typically at the scale of 10.0 μm or less. In current research trend, there have been an increasing number of investigations for the applications of x-ray units to organ-specific and whole-body radiation in dedicated small animal model study. In particular, scientists have identified that the integrated micro CT imagers can be commissioned as the dual-purpose unit for the high spatial resolution image acquisition and radiation delivery. As we all realized that small animal models are important and critical in several studies of experimental (or pre-clinical) radiation therapy research. In this paper, a Monte Carlo code (Penelope) was used to calculate the percentage depth dose distributions at different photon energy levels. Also the corresponding iso-dose contour curves were computed and plotted from the circular CT scanning geometry to study the desired dose conformity property. We note that the selected photon energy range that is included in this work is often included in the current commercial micro CT systems.

Cone beam breast CT technique provides true three dimensional (3D) images of breast anatomy; however the detectability of calcification is limited due to low exposure levels on each projection. In this study, we investigated the possibility of using anisotropic exposure distributions to improve the visibility of calcifications in the breast CT images. Our approach was to measure the CBCT projections with isotropic high and low exposures separately. Reconstruction was performed upon different combinations of these two sets of projection sequences to investigate the visibility change due to the limited-angle high exposure projections. Our preliminary results show that the visibility is improved with the number of high exposure projections in the combinations. In the future we will measure the CBCT projections with anisotropic exposures while keeping the total exposure constant.

We investigated the potential for digital tomosynthesis (DT) to reduce pediatric x-ray dose while maintaining image quality. We utilized the DT feature (VolumeRad^TM) on the GE Definium^TM 8000 flat panel system installed in the Winnipeg Children's Hospital. Facial bones, cervical spine, thoracic spine, and knee of children aged 5, 10, and 15 years were represented by acrylic phantoms for DT dose measurements. Effective dose was estimated for DT and for corresponding digital radiography (DR) and computed tomography (CT) patient image sets. Anthropomorphic phantoms of selected body parts were imaged by DR, DT, and CT. Pediatric radiologists rated visualization of selected anatomic features in these images. Dose and image quality comparisons between DR, DT, and CT determined the usefulness of tomosynthesis for pediatric imaging. CT effective dose was highest; total DR effective dose was not always lowest - depending how many projections were in the DR image set. For the cervical spine, DT dose was close to and occasionally lower than DR dose. Expert radiologists rated visibility of the central facial complex in a skull phantom as better than DR and comparable to CT. Digital tomosynthesis has a significantly lower dose than CT. This study has demonstrated DT shows promise to replace CT for some facial bones and spinal diagnoses. Other clinical applications will be evaluated in the future.

The performance optimization of tomosynthesis is very challenging as it involves multiple system parameters to be optimized towards multiple figures of merit (FOM). Common approach is to take a selected few FOMs and optimize them under more confined conditions. While this kind of study helps us to gain more insights, extra precautions are needed when one tries to generalize the conclusions. Several reported works have shown that increasing the scan angle improves the contrast to noise ratio (CNR), which made the authors conclude that from the CNR perspective, large scan angle has advantages over small angle in tomosynthesis. In this study, we investigated the dependence of CNR on the scan angle while other system parameters were fixed. We found that improvement of CNR with large scan angle in those published studies was actually due to reconstruction algorithm and associated filtering effect but not due to the scan angle itself. To reveal this property, we selected six filters to cover a board range of possible shapes, and showed CNR variations with different filters. Besides, we also studied the ML-EM and SART iterative reconstruction algorithms, and obtained their equivalent Fourier filters numerically. The change of the equivalent filter shapes of iterative methods at different scan angle explained the observed CNR dependence on the scan angles. We conclude that larger scan angle does not have any intrinsic CNR advantage over small one in tomosynthesis. The observed CNR gain at large angle is an effect from the reconstruction filters. Therefore CNR based optimization study need to be carried out without the potential bias from filters.

Chest tomosynthesis has recently been introduced to healthcare as a low-dose alternative to CT or as a tool for improved diagnostics in chest radiography with only a modest increase in radiation dose to the patient. However, no detailed description of the dosimetry for this type of examination has been presented. The aim of this work was therefore to investigate the dosimetry of chest tomosynthesis. The chest tomosynthesis examination was assumed to be performed using a stationary detector and a vertically moving x-ray tube, exposing the patient from different angles. The Monte Carlo based computer software PCXMC was used to determine the effective dose delivered to a standard-sized patient from various angles using different assumptions of the distribution of the effective dose over the different projections. The obtained conversion factors between input dose measures and effective dose for chest tomosynthesis for different angular intervals were then compared with the horizontal projection. The results indicate that the error introduced by using conversion factors for the PA projection in chest radiography for estimating the effective dose of chest tomosynthesis is small for normally sized patients, especially if a conversion factor between KAP and effective dose is used.

We evaluated the effects of scatter radiation on the reconstructed images in digital breast tomosynthesis. Projection images of a 6 cm anthropomorphic breast phantom were acquired using a Hologic prototype digital breast tomosynthesis system. Scatter intensities in projection images were sampled with a beam stop method. The scatter intensity at any pixel was obtained by two dimensional fitting. Primary-only projection images were generated by subtracting the scatter contributions from the original projection images. The 3-dimensional breast was reconstructed first based on original projection images which contained the contributions from both primary rays and scattered radiation using three different reconstruction algorithms. The same breast volume was reconstructed again using the same algorithms but based on primaryonly projection images. The image artifacts, pixel value difference to noise ratio (PDNR), and detected image features in these two sets of reconstructed slices were compared to evaluate the effects of scatter radiation. It was found that the scatter radiation caused inaccurate reconstruction of the x-ray attenuation property of the tissue. X-ray attenuation coefficients could be significantly underestimated in the region where scatter intensity is high. This phenomenon is similar to the cupping artifacts found in computed tomography. The scatter correction is important if accurate x-ray attenuation of the tissues is needed. No significant improvement in terms of numbers of detected image features was observed after scatter correction. More sophisticated phantom dedicated to digital breast tomosynthesis may be needed for further evaluation.

We have investigated the effect of non-isotropic blur in an indirect x-ray conversion screen in tomosynthesis imaging. To study this effect, we have implemented a screen model for angle-dependent x-ray incidence, and have validated the model using experimental as well as Monte-Carlo simulations reported in the literature. We investigated detector characteristics such as MTF, NPS and DQE, and we estimated system performance in a signal-known exactly detection task. We found that for such a screen, the frequency dependence of the MTF varies with x-ray source angle, while the frequency dependence of the NPS does not. Furthermore, as the x-ray source angle is increased, the DQE becomes more narrow and DQE(f=0) grows. We found that for a tomosynthesis scan angle of 90 degrees and a conversion screen thickness of 130 microns, detectability for small signals (radius=0.125 mm) was decreased by 13%, compared to signal radii above 0.5 mm. The magnitude of the degradation is expected to vary for different tomosynthesis configurations, such as scan angle and conversion screen thickness.

The ghosting and its recovery mechanisms in multilayer Selenium detectors for mammography are experimentally and theoretically investigated. The theoretical model considers accumulated trapped charges and their effects (trap filling, recombination, electric field profile, electric field dependent electron-hole pair creation), the carrier transport in the blocking layers, X-ray induced metastable deep trap center generations, and the effects of charge injection. The time dependent carrier detrapping and structural relaxation (recovery of meta-stable trap centers) are also considered. We simultaneously solve the continuity equations for both holes and electrons, trapping rate equations, and the Poisson's equation across the photoconductor for a step X-ray exposure by the Backward Euler finite difference method. The amount of ghosting strongly depends on the applied electric field and the initial carrier lifetimes. The dark current increases significantly with accumulated exposures. The sensitivity in a rested sample is recovered mainly by the carrier detrapping and the recombination of the injected carriers with the existing trapped carriers. The electric fields at the metal contacts increses with time in ghosting recovery process which leads to the initial increase of the dark current. The sensitivity is expected to recover almost fully by resting the sample longer than the recovery time constant of the meta-stable trap centers (the structural relaxation time constant), which is more than 24 hours. The theoretical model shows a very good agreement with the experimental relative sensitivity versus time and accumulative X-ray exposure characteristics.

This paper was not included in the print volume nor the cd. It is incorporated in this volume's online proceedings as paper 72585W.