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Proceedings Paper

Simulation and experimental validation of high-resolution test objects for evaluating a next-generation digital breast tomosynthesis prototype
Author(s): Trevor L. Vent; Bruno Barufaldi; Andrew D. A. Maidment
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Paper Abstract

Star pattern test objects are used to evaluate the high-contrast performance of imaging systems. These objects were used to investigate alternative scanning geometries for a prototype next-generation tomosynthesis (NGT) system. The NGT system has 2D planar source motion and linear detector motion, and is capable of myriad acquisition geometries. We designed a virtual star pattern with a voxel size of 5𝜇m, and used it to evaluate the spatial resolution performance of the NGT system for three different acquisition geometries. The Open Virtual Clinical Trials (OpenVCT) framework was used to simulate virtual star patterns for acquisition geometries of the NGT system. Simulated x-ray projections of the virtual phantom were used to create super-sampled 3D image reconstructions. Using the same acquisition geometries on the NGT system, a physical star pattern was imaged to create experimental 3D image reconstructions. The simulated and physical data were compared qualitatively by visual inspection, and quantitatively using an in-house metric. This metric computes the Fourier transform radially for one quadrant of the star pattern to discern the limit of spatial resolution (LSR) and the existence of aliasing. The results exhibit the same characteristics in terms of super-resolution and Moiré patterns (arising from aliasing) with visual inspection. The simulated LSR for the 12 conditions analyzed are all within 3% of the physical data. Aliasing was determined to be present in the same simulated image reconstructions as the experimental complements. Super-resolution is observed for two of the three NGT acquisition geometries in the experimental and simulated images.

Paper Details

Date Published: 1 March 2019
PDF: 12 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109480M (1 March 2019); doi: 10.1117/12.2511304
Show Author Affiliations
Trevor L. Vent, Univ. of Pennsylvania (United States)
Bruno Barufaldi, Univ. of Pennsylvania (United States)
Andrew D. A. Maidment, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

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