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Proceedings Paper

Compressed sensing algorithms for fan-beam CT image reconstruction
Author(s): Jun Zhang; Jun Wang; Guangwu Xu; Jean-Baptiste Thibault
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Paper Abstract

Compressed sensing can recover a signal that is sparse in some way from a small number of samples. For CT imaging, this has the potential to obtain good reconstruction from a smaller number of projections or views, thereby reducing the amount of patient radiation. In this work, we applied compressed sensing to fan beam CT image reconstruction , which is a special case of an important 3D CT problem (cone beam CT). We compared the performance of two compressed sensing algorithms, denoted as the LP and the QP, in simulation. Our results indicate that the LP generally provides smaller reconstruction error and converges faster, hence is more preferable.

Paper Details

Date Published: 16 March 2011
PDF: 10 pages
Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 796131 (16 March 2011); doi: 10.1117/12.877619
Show Author Affiliations
Jun Zhang, Univ. of Wisconsin-Milwaukee (United States)
Jun Wang, Univ. of Wisconsin-Milwaukee (United States)
Guangwu Xu, Univ. of Wisconsin-Milwaukee (United States)
Jean-Baptiste Thibault, GE Healthcare (United States)


Published in SPIE Proceedings Vol. 7961:
Medical Imaging 2011: Physics of Medical Imaging
Norbert J. Pelc; Ehsan Samei; Robert M. Nishikawa, Editor(s)

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