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An adaptive dynamic combined energy minimization model for few-view computed tomography reconstruction

Authors

  • Jun Feng,

    Corresponding author
    1. College of Computer, Sichuan University, Chengdu 610065, PR China
    2. Geomathematics Key Laboratory of Sichuan Province, Chengdu University of Technology, Chengdu 610059, PR China
    • College of Computer, Sichuan University, Chengdu 610065, PR China
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  • Jian-Zhou Zhang

    1. College of Computer, Sichuan University, Chengdu 610065, PR China
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Abstract

Recently, the potential harm of electromagnetic radiation used in computed tomography (CT) scanning has been paid much attention to. This makes the few-view CT reconstruction become an important issue in medical imaging. In this article, an adaptive dynamic combined energy minimization model is proposed for few-view CT reconstruction based on the compress sensing theory. The L2 energy of the image gradient and the total variation (TV) energy are combined, and the working regions of them are separated adaptively with a dynamic threshold. With the proposed model, the TV model's disadvantageous tendency of uniformly penalize the image gradient irrespective of the underlying image structures is overcome. Numerical experiments of the proposed model are performed with various insufficient data problems in fan-beam CT and suggest that both the reconstruction speed and quality of the results are generally improved. © 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 44–52, 2013.

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