Review of sparse optimization-based computed tomography image reconstruction from few-view projections

Wang Lin-Yuan; Liu Hong-Kui; Li Lei; Yan Bin; Zhang Han-Ming; Cai Ai-Long; Chen Jian-Lin; Hu Guo-En

doi:10.7498/aps.63.208702

Abstract

Computed tomography (CT) is a technology widely used in medicine and industrial non-destructive testing, and the image reconstruction algorithm is a core technology of CT. Now, the image reconstruction from few-view projections is a hot point in the study of reconstruction algorithm. With the advancements in theories and algorithms, the sparse optimization has recently been applied to few-view reconstruction for CT image, and shown to have a good performance in both accuracy and speed. In this paper, basic conclusions and classical algorithms in sparse optimization are introduced. Furthermore, the spare optimization based few-view reconstruction algorithms for CT image, in particular the main results and the values of spare optimization, are summarized. Finally, the future research direction of sparse optimization based few-view reconstruction for CT image is discussed.

Keywords:

Authors and contacts

1.
National Digital Switching System Engineering and Technological Research Center, Zhengzhou 450002, China;
2.
Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116000, China
Funds: Project supported by the National High Technology Research and Development Program of China (Grant No. 2012AA011603) and the National Natural Science Foundation of China (Grant No. 61372172).

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Cited By

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[9]
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Vol. 63, Issue 20 - 2014-10-20

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