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Proceedings Paper

Choosing anisotropic voxel dimensions in optimization-based image reconstruction for limited angle CT
Author(s): C. Sheng; R. Chaudhari; Sean D. Rose; Emil Y. Sidky; Xiaochuan Pan
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Paper Abstract

Resolution of reconstructions in limited angle X-ray computed tomography (CT) is inherently anisotropic due to the limited angular range of acquired projections. This justifies the use of anisotropic voxels in limited angle image reconstruction. For analytic reconstruction algorithms, this only changes the intervals at which the reconstruction is sampled, but for optimization-based image reconstruction, changing the voxel dimensions redefines the reconstruction optimization problem and can have pronounced effects on the reconstructed image. In this work we investigate the choice of anisotropic voxel dimensions in optimization-based image reconstruction for limited angle CT. In particular, a 2D simulation study is performed to assess the optimal choice of pixel dimension in the longitudinal direction - the direction of lowest resolution. It is demonstrated that as this pixel dimension is decreased, deterioration of system matrix conditioning can lead to severe distortion in reconstructions performed with low regularization strength. This conditioning issue occurs at approximately the point where the number of pixels is equal to the number of measurements. While the distortion can be mitigated by increasing regularization, our results suggest that there are structures which are only resolvable by using even smaller voxel sizes.

Paper Details

Date Published: 9 March 2017
PDF: 5 pages
Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101322X (9 March 2017); doi: 10.1117/12.2254292
Show Author Affiliations
C. Sheng, The Univ. of Chicago (United States)
R. Chaudhari, The Univ. of Chicago (United States)
Sean D. Rose, The Univ. of Chicago (United States)
Emil Y. Sidky, The Univ. of Chicago (United States)
Xiaochuan Pan, The Univ. of Chicago (United States)


Published in SPIE Proceedings Vol. 10132:
Medical Imaging 2017: Physics of Medical Imaging
Thomas G. Flohr; Joseph Y. Lo; Taly Gilat Schmidt, Editor(s)

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