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Proceedings Paper

Multi-slice and multi-frame image reconstruction by predictive compressed sensing
Author(s): Jun Zhang; Jun Wang; Guangwu Xu; Jean-Baptiste Thibault
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Paper Abstract

In this paper, we describe a prediction based compressed-sensing approach for multi-slice (same time, different locations) or multi-frame (same location, different time) CT image reconstruction. In this approach, the second slice/frame of a pair of consecutive slices/frames is reconstructed through reconstructing the prediction error image between the first and second slice/frame, using compressed-sensing. This approach exploits the inter-slice/inter-frame correlation and the higher degree of sparsity of the prediction error image to achieve more efficient image reconstruction, i.e., fewer projections for the same image quality or higher image quality for the same number of projections. The efficacy of our approach is demonstrated through simulation results.

Paper Details

Date Published: 24 February 2012
PDF: 6 pages
Proc. SPIE 8314, Medical Imaging 2012: Image Processing, 83144M (24 February 2012); doi: 10.1117/12.911150
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. 8314:
Medical Imaging 2012: Image Processing
David R. Haynor; Sébastien Ourselin, Editor(s)

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