Regularization in Tomographic Reconstruction Using Prozimal Forward-Backward Algorithm

摘要：

Recently, there are many approaches to tomographic reconstruction that consist of minimizing the sum of a residual energy and a regularized function using some prior information. Usually great efforts are expended for specific models with different regularizations. In this paper, taking the advantage of the proximity operators and operator splitting in convex analytical tools, we provide a systematic analysis of such generic models. Then using proximal forward-backward method, an iterative algorithm is given to solve them. And we provide two examples with different regularized function to demonstrate how this generic tomographic construction scheme works.

关键词： prozimal operator regularization tomographic reconstruction

作者: WANG Li-yan WEI Zhi-hui

作者单位: Department of Mathematics Southeast University Nanjing,China Department of Computer Science Nanjing Department of Computer Science Nanjing University of Science & Technology Nanjing,China

会议类型: 国际会议

会议名称: The 3rd International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2009)(第三届生物信息与生物医学工程国际会议)

会议地点: 北京

会议语种:英文

页码: 1-4

在线出版日期: 2009-06-11（万方平台首次上网日期，不代表论文的发表时间）