This PDF file contains the front matter associated with SPIE Proceedings Volume 10483, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

Scanning laser ophthalmoscopy (SLO) provides high-speed, noninvasive en face imaging of the retinal fundus. Optical coherence tomography (OCT) is the current “gold-standard” for ophthalmic diagnostic imaging and enables depth-resolved visualization of ophthalmic structures and image-based surrogate biomarkers of disease. We present a compact optical and mechanical design for handheld spectrally encoded coherence tomography and reflectometry (SECTR) for multimodality en face spectrally encoded reflectometry (SER) and cross-sectional OCT imaging. We custom-designed a double-pass telecentric scan lens, which halves the size of 4-f optical relays and allowed us to reduce the footprint of our SECTR scan-head by a factor of >2.7x (volume) over our previous design. The double-pass scan lens was optimized for diffraction-limited performance over a ±10° scan field. SECTR optics and optomechanics were combined in a compact rapid-prototyped enclosure with dimensions 87 x 141.8 x 137 mm (w x h x d). SECTR was implemented using a custom-built 400 kHz 1050 nm swept-source. OCT and SER were simultaneously digitized on dual input channels of a 4 GS/s digitizer at 1.4 GS/s per channel. In vivo human en face SER and cross-sectional OCT images were acquired at 350 fps. OCT volumes of 1000 B-scans were acquired in 2.86 s. We believe clinical translation of our compact handheld design will benefit point-of-care ophthalmic diagnostics in patients who are unable to be imaged on conventional slit-lamp based systems, such as infants and the bedridden. When combined with multi-volumetric registration methods, handheld SECTR will have advantages in motion-artifact free imaging over existing handheld technologies.

Catheter-based Optical Coherence Tomography (OCT) devices allow real-time and comprehensive imaging of the human esophagus. Hence, they provide the potential to overcome some of the limitations of endoscopy and biopsy, allowing earlier diagnosis and better prognosis for esophageal adenocarcinoma patients. However, the large number of images produced during every scan makes manual evaluation of the data exceedingly difficult. In this study, we propose a fully automated tissue characterization algorithm, capable of discriminating normal tissue from Barrett’s Esophagus (BE) and dysplasia through entire three-dimensional (3D) data sets, acquired in vivo. The method is based on both the estimation of the scatterer size of the esophageal epithelial cells, using the bandwidth of the correlation of the derivative (COD) method, as well as intensity-based characteristics. The COD method can effectively estimate the scatterer size of the esophageal epithelium cells in good agreement with the literature. As expected, both the mean scatterer size and its standard deviation increase with increasing severity of disease (i.e. from normal to BE to dysplasia). The differences in the distribution of scatterer size for each tissue type are statistically significant, with a p value of < 0.0001. However, the scatterer size by itself cannot be used to accurately classify the various tissues. With the addition of intensity-based statistics the correct classification rates for all three tissue types range from 83 to 100% depending on the lesion size.

Limited visualization of semi-transparent structures in the eye remains a critical barrier to improving clinical outcomes and developing novel surgical techniques. While increases in imaging speed has enabled intraoperative optical coherence tomography (iOCT) imaging of surgical dynamics, several critical barriers to clinical adoption remain. Specifically, these include (1) static field-of-views (FOVs) requiring manual instrument-tracking; (2) high frame-rates require sparse sampling, which limits FOV; and (3) small iOCT FOV also limits the ability to co-register data with surgical microscopy. We previously addressed these limitations in image-guided ophthalmic microsurgery by developing microscope-integrated multimodal intraoperative swept-source spectrally encoded scanning laser ophthalmoscopy and optical coherence tomography. Complementary en face images enabled orientation and coregistration with the widefield surgical microscope view while OCT imaging enabled depth-resolved visualization of surgical instrument positions relative to anatomic structures-of-interest. In addition, we demonstrated novel integrated segmentation overlays for augmented-reality surgical guidance. Unfortunately, our previous system lacked the resolution and optical throughput for in vivo retinal imaging and necessitated removal of cornea and lens. These limitations were predominately a result of optical aberrations from imaging through a shared surgical microscope objective lens, which was modeled as a paraxial surface. Here, we present an optimized intraoperative spectrally encoded coherence tomography and reflectometry (iSECTR) system. We use a novel lens characterization method to develop an accurate model of surgical microscope objective performance and balance out inherent aberrations using iSECTR relay optics. Using this system, we demonstrate in vivo multimodal ophthalmic imaging through a surgical microscope

Screening for ocular diseases, such as glaucoma and keratoconus, includes measuring the eye-globe intraocular pressure (IOP) and corneal biomechanical properties. However, currently available clinical tools cannot quantify corneal tissue material parameters, which can provide critical information for detecting diseases and evaluating therapeutic outcomes. Here, we demonstrate measurement of eye-globe IOP, corneal elasticity, and corneal geometry of in situ porcine corneas with a technique termed applanation optical coherence elastography (Appl-OCE) with single instrument. We utilize an ultrafast phase-sensitive optical coherence tomography system comprised of a 4X buffered Fourier domain mode-locked swept source laser with an Ascan rate of ~1.5 MHz and a 7.3 kHz resonant scanner. The IOP was measured by imaging the response of in situ porcine corneas to a large force air-puff. As with other noncontact tonometers, the time when the cornea was applanated during the inwards and outwards motion was correlated to a measure air-pressure temporal profile. The IOP was also measured with a commercially available rebound tonometer for comparison. The stiffness of the corneas was assessed by directly imaging and analyzing the propagation of a focused micro air-pulse induced elastic wave, and the corneal geometry was obtained from the OCT structural image. Our results show that corneal thickness decreased as IOP increased, and that corneal stiffness increased with IOP. Moreover, the IOP measurements made by Appl-OCE were more closely correlated with the artificially set IOP than the rebound tonometer, demonstrating the capabilities of Appl-OCE to measure corneal stiffness, eye-globe IOP, and corneal geometry with a single instrument.

Optical Coherence Tomography (OCT) has made it into the clinic in the last decade with systems based on bulk optical components. The next disruptive step will be the introduction of handheld OCT systems. Photonic Integrated Circuit (PIC) technology is the key enabler for this further miniaturization. PIC technology allows signal processing on a stable platform and the implementation of a common path interferometer in that same platform creates a robust fully integrated OCT system with a flexible fiber probe. In this work the first PIC based handheld and integrated common path based spectral domain OCT system is described and demonstrated. The spectrometer in the system is based on an Arrayed Waveguide Grating (AWG) and fully integrated with the CCD and a fiber probe into a system operating at 850 nm. The AWG on the PIC creates a 512 channel spectrometer with a resolution of 0.22 nm enabling a high speed analysis of the full A-scan. The silicon nitride based proprietary waveguide technology (TriPleX^TM) enables low loss complex photonic structures from the visible (405 nm) to IR (2350 nm) range, making it a unique candidate for OCT applications. Broadband AWG operation from visible to 1700 nm has been shown in the platform and Photonic Design Kits (PDK) are available enabling custom made designs in a system level design environment. This allows a low threshold entry for designing new (OCT) designs for a broad wavelength range.

Most flying-spot Optical Coherence Tomography (OCT) and Optical Coherence Microscopy (OCM) systems use a symmetric confocal geometry, where the detection path retraces the illumination path starting from and ending with the spatial mode of a single mode optical fiber. Here, we describe a visible light OCM instrument that breaks this symmetry to improve transverse resolution without sacrificing collection efficiency in scattering tissue. This was achieved by overfilling a 0.3 numerical aperture (NA) water immersion objective on the illumination path, while maintaining a conventional Gaussian mode detection path (1/e² intensity diameter ~0.82 Airy disks), enabling ~1.1 μm full-width at half-maximum (FWHM) transverse resolution. At the same time, a ~0.9 μm FWHM axial resolution in tissue, achieved by a broadband visible light source, enabled femtoliter volume resolution. We characterized this instrument according to paraxial coherent microscopy theory, and then used it to image the meningeal layers, intravascular red blood cell-free layer, and myelinated axons in the mouse neocortex in vivo through the thinned skull. Finally, by introducing a 0.8 NA water immersion objective, we improved the lateral resolution to 0.44 μm FWHM, which provided a volumetric resolution of ~0.2 fL, revealing cell bodies in cortical layer I of the mouse brain with OCM for the first time.

Optical Coherence Tomography (OCT) imaging of living subjects offers millimeters depth of penetration into tissue while maintaining high spatial resolution. However, because most molecular biomarkers do not produce inherent OCT contrast signals, exogenous contrast agents must be employed to achieve molecular imaging. Here we demonstrate that microbeads (μBs) can be used as effective contrast agents to target cellular biomarkers in lymphatic vessels and can be detected by OCT using a phase variance algorithm. We applied this technique to image the molecular dynamics of lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1) in vivo, which showed significant down-regulation during tissue inflammation.

The attenuation coefficient (AC) is a property related to the microstructure of tissue on a wavelength scale that can be estimated from optical coherence tomography (OCT) data. Since the OCT signal sensitivity is affected by the finite spectrometer/detector resolution called roll-off and the shape of the focused beam in the sample arm, ignoring these effects leads to severely biased estimates of AC. Previously, the signal intensity dependence on these factors has been modeled. In this paper, we study the dependence of the estimated AC on the beam-shape and focus depth experimentally. A method is presented to estimate the axial point spread function model parameters by fitting the OCT signal model for single scattered light to the averaged A-lines of multiple B-scans obtained from a homogeneous single-layer phantom. The estimated model parameters were used to compensate the signal for the axial point spread function and roll-off in order to obtain an accurate estimate of AC. The result shows a significant improvement in the accuracy of the estimation of AC after correcting for the shape of the OCT beam.

A commercial ophthalmic laser system (R;GEN, Lutronic Corp) was integrated with a swept-source optical coherence tomography (OCT) imaging system for real-time tissue temperature monitoring. M-scan OCT images were acquired during laser-pulse radiation, and speckle variance OCT (svOCT) images were analyzed to deduce temporal signal variations related to tissue temperature change from laser-pulse radiation. A phantom study shows that svOCT magnitude increases abruptly after laser pulse radiation and recovered exponentially, and the peak intensity of svOCT image was linearly dependent on pulse laser energy until it saturates. A study using bovine iris also showed signal variation dependence on the laser pulse radiation, and the variation was more distinctive with higher energy level.

Optical coherence tomography (OCT) is a powerful biomedical imaging technology that relies on the coherent detection of backscattered light to image tissue morphology in vivo. As a consequence, OCT is susceptible to coherent noise, known as speckle noise, which imposes significant limitations on its diagnostic capabilities. Here we show Speckle- Modulating OCT (SM-OCT), a method based purely on light manipulation, which can remove speckle noise, including noise originating from sample multiple back-scattering. SM-OCT accomplishes this by creating and averaging an unlimited number of scans with uncorrelated speckle patterns, without compromising spatial resolution. The uncorrelated speckle patterns are created by scrambling the phase of the light with sub-resolution features using a moving ground-glass diffuser in the optical path of the sample arm. This method can be implemented in existing OCTs as a relatively low-cost add-on. SM-OCT speckle statistics follow the expected decrease in speckle contrast as the number of averaged scans increases. Within a scattering phantom, SM-OCT provides a 2.5-fold increase in effective resolution compared to conventional OCT. Using SM-OCT, we reveal small structures in the tissues of living animals, such as the inner stromal structure of a live mouse cornea, the fine structures inside the mouse pinna, and sweat ducts and Meissner’s corpuscle in the human fingertip skin – features that are otherwise obscured by speckle noise when using conventional OCT or OCT with current state of the art speckle reduction methods. Our results indicate that SM-OCT has the potential to improve the current diagnostic and intra-operative capabilities of OCT.

In this communication, we present a proof-of-concept polarization-sensitive Optical Coherence Tomography (PS-OCT) which can be used to characterize the retardance and the axis orientation of a linear birefringent sample. This module configuration is an improvement from our previous work^{1, 2} since it encodes the two polarization channels on the optical path difference, effectively carrying out the polarization measurements simultaneously (snapshot measurement), whilst retaining all the advantages (namely the insensitivity to environmental parameters when using SM fibers) of these two previous configurations. Further progress consists in employing Master Slave OCT technology,³ which is used to automatically compensate for the dispersion mismatch introduced by the elements in the module. This is essential given the encoding of the polarization states on two different optical path lengths, each of them having dissimilar dispersive properties. By utilizing this method instead of the commonly used re-linearization and numerical dispersion compensation methods an improvement in terms of the calculation time required can be achieved.

In this paper the benefits in terms of operation time that Master/Slave (MS) implementation of optical coherence tomography can bring in comparison to Gabor fused (GF) employing conventional fast Fourier transform based OCT are presented. The Gabor Fusion/Master Slave Optical Coherence Tomography architecture proposed here does not need any data stitching. Instead, a subset of en-face images is produced for each focus position inside the sample to be imaged, using a reduced number of theoretically inferred Master masks. These en-face images are then assembled into a final volume. When the channelled spectra are digitized into 1024 sampling points, and more than 4 focus positions are required to produce the final volume, the Master Slave implementation of the instrument is faster than the conventional fast Fourier transform based procedure.

Retinal layer shape and thickness are one of the main indicators in the diagnosis of ocular diseases. We present an active contour approach to localize intra-retinal boundaries of eight retinal layers from OCT images. The initial locations of the active contour curves are determined using a Viterbi dynamic programming method. The main energy function is a Chan-Vese active contour model without edges. A boundary term is added to the energy function using an adaptive weighting method to help curves converge to the retinal layer edges more precisely, after evolving of curves towards boundaries, in final iterations. A wavelet-based denoising method is used to remove speckle from OCT images while preserving important details and edges. The performance of the proposed method was tested on a set of healthy and diseased eye SD-OCT images. The experimental results, compared between the proposed method and the manual segmentation, which was determined by an optometrist, indicate that our method has obtained an average of 95.29%, 92.78%, 95.86%, 87.93%, 82.67%, and 90.25% respectively, for accuracy, sensitivity, specificity, precision, Jaccard Index, and Dice Similarity Coefficient over all segmented layers. These results justify the robustness of the proposed method in determining the location of different retinal layers.

Design of optical imaging systems requires careful balancing of lens aberrations to optimize the point-spread function (PSF) and minimize field distortions. Aberrations and distortions are a result of both lens geometry and glass material. While most lens manufacturers provide optical models to facilitate system-level simulation, these models are often not reflective of true system performance because of manufacturing tolerances. Optical design can be further confounded when achromatic or proprietary lenses are employed. Achromats are ubiquitous in systems that utilize broadband sources due to their superior performance in balancing chromatic aberrations. Similarly, proprietary lenses may be custom-designed for optimal performance, but lens models are generally not available. Optical coherence tomography (OCT) provides non-contact, depth-resolved imaging with high axial resolution and sensitivity. OCT has been previously used to measure the refractive index of unknown materials. In a homogenous sample, the group refractive index is obtained as the ratio between the measured optical and geometric thicknesses of the sample. In heterogenous samples, a method called focus-tracking (FT) quantifies the effect of focal shift introduced by the sample. This enables simultaneous measurement of the thickness and refractive index of intermediate sample layers. Here, we extend the mathematical framework of FT to spherical surfaces, and describe a method based on OCT and FT for full characterization of lens geometry and refractive index. Finally, we validate our characterization method on commercially available singlet and doublet lenses.

We report a new speckle noise removal algorithm in optical coherence tomography (OCT). Though wavelet domain thresholding algorithms have demonstrated superior advantages in suppressing noise magnitude and preserving image sharpness in OCT, the wavelet tree structure has not been investigated in previous applications. In this work, we propose an adaptive wavelet thresholding algorithm via exploiting the tree structure in wavelet coefficients to remove the speckle noise in OCT images. The threshold for each wavelet band is adaptively selected following a special rule to retain the structure of the image across different wavelet layers. Our results demonstrate that the proposed algorithm outperforms conventional wavelet thresholding, with significant advantages in preserving image features.

We report that wide field-of-view (FOV) optical coherence tomography images with high lateral resolution can be obtained by using superresolution and 3D image stitching techniques. About 3 times lateral resolution improvement from 6.20 μm to 2.19 μm using a focusing lens of 0.08 numerical aperture has been demonstrated. With such lens the FOV is generally small owing to off-axis focusing degradation. To enlarge the FOV while maintaining high lateral resolution, 3D image stitching technique is introduced to effectively reconstruct an ultra-wide FOV 3D image of 2.10x1.15 mm² lateral area from ten C-scans of 500×500 μm² FOV. Improved FOV with high lateral resolution should benefit various biomedical imaging applications.

Swept Source optical coherence tomography (SS-OCT) is an important imaging modality for both medical and industrial diagnostic applications. A cross-sectional SS-OCT image is obtained by applying an inverse discrete Fourier transform (DFT) to axial interferograms measured in the frequency domain (k-space). This inverse DFT is typically implemented as a fast Fourier transform (FFT) that requires the data samples to be equidistant in k-space. As the frequency of light produced by a typical wavelength-swept laser is nonlinear in time, the recorded interferogram samples will not be uniformly spaced in k-space. Many image reconstruction methods have been proposed to overcome this problem. Most such methods rely on oversampling the measured interferogram then use either hardware, e.g., Mach-Zhender interferometer as a frequency clock module, or software, e.g., interpolation in k-space, to obtain equally spaced samples that are suitable for the FFT. To overcome the problem of nonuniform sampling in k-space without any need for interferogram oversampling, an earlier method demonstrated the use of the nonuniform discrete Fourier transform (NDFT) for image reconstruction in SS-OCT. In this paper, we present a more accurate method for SS-OCT image reconstruction from nonuniform samples in k-space using a scaled nonuniform Fourier transform. The result is demonstrated using SS-OCT images of Axolotl salamander eggs.

The optimization of AlGaInP/GaInPAs MQW heterostructure MOCVD growth as well as the improvements of active channel formation and P-contact deposition technologies made it possible to increase significantly external differential efficiency (up to 0.5 mW/mA) and CW catastrophic optical damage threshold (up to 40 mW) of spatially single-mode superluminescent diodes (SLDs) with central wavelength of 675 nm. Preliminary life time tests demonstrated high reliability of the devices at output power 30 mW. The relations of spectral and power characteristics of the SLDs as well as SLDs with central wavelengths of about 660 nm and 690 nm on active channel length, pumping level and temperature were studied. The results of mathematical modeling of combined light sources output parameters that could be made with SLDs and a broadband SM fiber coupler, are presented.

Segmentation of spectral-domain Optical Coherence Tomography (SD-OCT) images facilitates visualization and quantification of sub-retinal layers for diagnosis of retinal pathologies. However, manual segmentation is subjective, expertise dependent, and time-consuming, which limits applicability of SD-OCT. Efforts are therefore being made to implement active-contours, artificial intelligence, and graph-search to automatically segment retinal layers with accuracy comparable to that of manual segmentation, to ease clinical decision-making. Although, low optical contrast, heavy speckle noise, and pathologies pose challenges to automated segmentation. Graph-based image segmentation approach stands out from the rest because of its ability to minimize the cost function while maximising the flow. This study has developed and implemented a shortest-path based graph-search algorithm for automated intraretinal layer segmentation of SD-OCT images. The algorithm estimates the minimal-weight path between two graph-nodes based on their gradients. Boundary position indices (BPI) are computed from the transition between pixel intensities. The mean difference between BPIs of two consecutive layers quantify individual layer thicknesses, which shows statistically insignificant differences when compared to a previous study [for overall retina: p = 0.17, for individual layers: p > 0.05 (except one layer: p = 0.04)]. These results substantiate the accurate delineation of seven intraretinal boundaries in SD-OCT images by this algorithm, with a mean computation time of 0.93 seconds (64-bit Windows10, core i5, 8GB RAM). Besides being self-reliant for denoising, the algorithm is further computationally optimized to restrict segmentation within the user defined region-of-interest. The efficiency and reliability of this algorithm, even in noisy image conditions, makes it clinically applicable.

Based on the analysis of the noise source in the optical coherence tomography (OCT) system, a fractional integral denoising algorithm is proposed to denoise the OCT image. The algorithm is simple and easy to implement, and the experiment is compared with the median filter and Wiener filter method. The results show that the algorithm can effectively preserve the important detail information in the OCT image while effectively removing the noise, so that the detail of the image is clear and the image quality can be improved, which indicates that the method can achieve the purpose of reducing the image noise.

Quantitative measurement of blood flow velocity in capillaries is challenging due to their small size (around 5-10 μm), and the discontinuity and single-file feature of RBCs flowing in a capillary. In this work, we present a phase-resolved Optical Coherence Tomography (OCT) method for accurate measurement of the red blood cell (RBC) speed in cerebral capillaries. To account for the discontinuity of RBCs flowing in capillaries, we applied an M-mode scanning strategy that repeated A-scans at each scanning position for an extended time. As the capillary size is comparable to the OCT resolution size (3.5×3.5×3.5μm), we applied a high pass filter to remove the stationary signal component so that the phase information of the dynamic component (i.e. from the moving RBC) could be enhanced to provide an accurate estimate of the RBC axial speed. The phase-resolved OCT method accurately quantifies the axial velocity of RBC’s from the phase shift of the dynamic component of the signal. We validated our measurements by RBC passage velocimetry using the signal magnitude of the same OCT time series data. These proposed method of capillary velocimetry proved to be a robust method of mapping capillary RBC speeds across the micro-vascular network.

In brain cancer surgery, it is critical to achieve extensive resection without compromising adjacent healthy, noncancerous regions. Various technological advances have made major contributions in imaging, including intraoperative magnetic imaging (MRI) and computed tomography (CT). However, these technologies have pros and cons in providing quantitative, real-time and three-dimensional (3D) continuous guidance in brain cancer detection. Optical Coherence Tomography (OCT) is a non-invasive, label-free, cost-effective technique capable of imaging tissue in three dimensions and real time. The purpose of this study is to reliably and efficiently discriminate between non-cancer and cancerinfiltrated brain regions using OCT images. To this end, a mathematical model for quantitative evaluation known as the Blind End-Member and Abundances Extraction method (BEAE). This BEAE method is a constrained optimization technique which extracts spatial information from volumetric OCT images. Using this novel method, we are able to discriminate between cancerous and non-cancerous tissues and using logistic regression as a classifier for automatic brain tumor margin detection. Using this technique, we are able to achieve excellent performance using an extensive cross-validation of the training dataset (sensitivity 92.91% and specificity 98.15%) and again using an independent, blinded validation dataset (sensitivity 92.91% and specificity 86.36%). In summary, BEAE is well-suited to differentiate brain tissue which could support the guiding surgery process for tissue resection.

It is important to provide timely information to surgeons on diagnosis of a suspicious ovarian tissue before excision to avoid unnecessary surgery, especially for young women. In this report, we introduce a new 3-D surface mapping technique to map ovarian tissue scattering properties by fitting the swept-source optical coherence tomography (SS-OCT) signals to a scattering model. We observed that lower scattering coefficients and heterogeneous spatial distribution were associated with malignant ovarian tissues, and higher scattering coefficients and homogeneous spatial distribution indicated benign ovarian tissues. The initial results suggest that the 3-D scattering map has potential to be an effective tool to characterize normal and malignant ovarian tissues.

Polarization-sensitive optical coherence tomography (PS-OCT) is capable of measuring tissue birefringence. It has been widely applied to access the birefringence in tissues such as skin and cartilage. The vocal cord tissue consists of three anatomical layers from the surface to deep inside, the epithelium that contains almost no collagen, the lamina propria that is composed with abundant collagen, and the vocalis muscle layer. Due to the variation in the organization of collagen fibers, the different tissue layers show different tissue birefringence, which can be evaluated by PS-OCT phase retardation measurement. Furthermore, collagen fibers in healthy connective tissues are usually well organized, which provides relatively high birefringence. When the collagen organization is destroyed by diseases such as tumor, the birefringence of the tissue will decrease. In this study, a rabbit laryngeal tumor model with different stages of tumor progression is investigated ex-vivo by PS-OCT. The PS-OCT images show a gradual decrease in birefringence from normal tissue to severe tumor tissue. A phase retardation slope-based analysis is conducted to distinguish the epithelium, lamina propria, and muscle layers, respectively. The phase retardation slope quantifies the birefringence in different layers. The quantitative study provides a more detailed comparison among different stages of the rabbit laryngeal tumor model. The PS-OCT result is validated by the corresponding histology images of the same samples.

Brain tissue differentiation is highly demanded in neurosurgeries, i.e. tumor resection. Exact navigation during the surgery is essential in order to guarantee best life quality afterwards. So far, no suitable method has been found that perfectly covers this demands. With optical coherence tomography (OCT), fast three dimensional images can be obtained in vivo and contactless with a resolution of 1-15 μm. With these specifications OCT is a promising tool to support neurosurgeries. Here, we investigate ex vivo samples of meningioma, healthy white and healthy gray matter in a preliminary study towards in vivo brain tumor removal assistance. Raw OCT images already display structural variations for different tissue types, especially meningioma. But, in order to achieve neurosurgical guidance directly during resection, an automated differentiation approach is desired. For this reason, we employ different texture feature based algorithms, perform a Principal Component Analysis afterwards and then train a Support Vector Machine classifier. In the future we will try different combinations of texture features and perform in vivo measurements in order to validate our findings.