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Proceedings Paper

Optimization-based reconstruction for correcting non-linear partial volume artifacts in CT
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Paper Abstract

In this work, we investigate the non-linear partial volume (NLPV) effect caused by sub-detector sampling in CT. A non-linear log-sum of exponential data model is employed to describe the NLPV effect. Leveraging our previous work on multispectral CT reconstruction dealing with a similar non-linear data model, we propose an optimization-based reconstruction method for correcting the NLPV artifacts by numerically inverting the non-linear model through solving a non-convex optimization program. A non-convex Chambolle-Pock (ncCP) algorithm is developed and tailored to the non-linear data model. Simulation studies are carried out with both discrete and continuous FORBILD head phantom with one high-contrast ear section on the right side, based on a circular 2D fan-beam geometry. The results suggest that, under the data condition in this work, the proposed method can effectively reduce or eliminate the NLPV artifacts caused by the sub-detector ray integration.

Paper Details

Date Published: 1 March 2019
PDF: 6 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109482Q (1 March 2019); doi: 10.1117/12.2512917
Show Author Affiliations
Xin Liu, The Univ. of Chicago (United States)
Shenzhen Univ. (China)
Buxin Chen, The Univ. of Chicago (United States)
Zheng Zhang, The Univ. of Chicago (United States)
Dan Xia, 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. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

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