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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 4850317, 8 pages
Research Article

Relaxation Factor Optimization for Common Iterative Algorithms in Optical Computed Tomography

1School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, China
2Sichuan Province Key Laboratory of Signal and Information Processing, Xihua University, Chengdu 610039, China
3Hiroshima Institute of Technology, Hiroshima 731-5193, Japan

Correspondence should be addressed to Wenbo Jiang

Received 12 April 2017; Revised 6 June 2017; Accepted 12 June 2017; Published 16 July 2017

Academic Editor: Eric Feulvarch

Copyright © 2017 Wenbo Jiang and Xiaohua Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Optical computed tomography technique has been widely used in pathological diagnosis and clinical medicine. For most of optical computed tomography algorithms, the relaxation factor plays a very important role in the quality of the reconstruction image. In this paper, the optimal relaxation factors of the ART, MART, and SART algorithms for bimodal asymmetrical and three-peak asymmetrical tested images are analyzed and discussed. Furthermore, the reconstructions with Gaussian noise are also considered to evaluate the antinoise ability of the above three algorithms. The numerical simulation results show that the reconstruction errors and the optimal relaxation factors are greatly influenced by the Gaussian noise. This research will provide a good theoretical foundation and reference value for pathological diagnosis, especially for ophthalmic, dental, breast, cardiovascular, and gastrointestinal diseases.