This work presents a novel computed tomography reconstruction method for few-view problem based on a compound method. To overcome the disadvantages of total variation (TV) minimization method, we use a high-order norm coupled within TV and the numerical scheme for our method is given. We use the root mean square error as a referee. The numerical experiments demonstrate that our method achieves better performance than existing reconstruction methods, including filtered back projection, expectation maximization, and TV with projection on convex sets. (c) 2013 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 23, 249-255, 2013
机构:
Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
Chang, Qianshun
Tai, Xuecheng
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Nanyang Technol Univ, Sch Phys & Math Sci, Singapore 637371, Singapore
Univ Bergen, Dept Math, N-5008 Bergen, NorwayChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
Tai, Xuecheng
Xing, Lily
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机构:
Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
机构:
Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
Chang, Qianshun
Tai, Xuecheng
论文数: 0引用数: 0
h-index: 0
机构:
Nanyang Technol Univ, Sch Phys & Math Sci, Singapore 637371, Singapore
Univ Bergen, Dept Math, N-5008 Bergen, NorwayChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
Tai, Xuecheng
Xing, Lily
论文数: 0引用数: 0
h-index: 0
机构:
Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R ChinaChinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China