Journal of shanghai Jiaotong University (Science) ›› 2015, Vol. 20 ›› Issue (2): 202-208.doi: 10.1007/s12204-015-1608-9

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An Iterative Algorithm for Computed Tomography Image Reconstruction from Limited-Angle Projections

An Iterative Algorithm for Computed Tomography Image Reconstruction from Limited-Angle Projections

SUN Yu-li (孙玉立), TAO Jin-xu* (陶进绪), CHEN Hao (陈浩), LIU Cong-gui (刘从桂)   

  1. (Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China)
  2. (Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230027, China)
  • Published:2015-04-02
  • Contact: TAO Jin-xu (陶进绪) E-mail:tjingx@ustc.edu.cn

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.

Key words: computed tomography| limited-angle reconstruction| Papoulis-Gerchberg algorithm

摘要: 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.

关键词: computed tomography| limited-angle reconstruction| Papoulis-Gerchberg algorithm

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