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An iterative algorithm for computed tomography image reconstruction from limited-angle projections

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Abstract

In application of tomography imaging, limited-angle problem is a quite practical and important issue. In this paper, an iterative reprojection-reconstruction (IRR) algorithm using a modified Papoulis-Gerchberg (PG) iterative scheme is developed for reconstruction from limited-angle projections which contain noise. The proposed algorithm has two iterative update processes, one is the extrapolation of unknown data, and the other is the modification of the known noisy observation data. And the algorithm introduces scaling factors to control the two processes, respectively. The convergence of the algorithm is guaranteed, and the method of choosing the scaling factors is given with energy constraints. The simulation result demonstrates our conclusions and indicates that the algorithm proposed in this paper can obviously improve the reconstruction quality.

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Authors and Affiliations

  1. Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, 230027, China

    Yu-li Sun  (孙玉立), Jin-xu Tao  (陶进绪), Hao Chen  (陈 浩) & Cong-gui Liu  (刘从桂)

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  1. Yu-li Sun  (孙玉立)
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  2. Jin-xu Tao  (陶进绪)
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  3. Hao Chen  (陈 浩)
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  4. Cong-gui Liu  (刘从桂)
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Correspondence to Jin-xu Tao  (陶进绪).

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Sun, Yl., Tao, Jx., Chen, H. et al. An iterative algorithm for computed tomography image reconstruction from limited-angle projections. J. Shanghai Jiaotong Univ. (Sci.) 20, 202–208 (2015). https://doi.org/10.1007/s12204-015-1608-9

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  • DOI: https://doi.org/10.1007/s12204-015-1608-9

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