Sparse angular CT reconstruction using non-local means based iterative-correction POCS

详细信息    查看全文

• 作者：Jing Huang^a ; ^{hjing@fimmu.com} ; Jianhua Ma ; ^a ; ^{mhn_1998@163.com} ; Nan Liu^a ; ^{lnan@fimmu.com} ; Hua Zhang^a ; ^{xinsier@gmail.com} ; Zhaoying Bian^a ; ^{zybian@fimmu.com} ; Yanqiu Feng^a ; ^{foree@fimmu.com} ; Qianjin Feng^a ; ^{fengqj@fimmu.com} ; Wufan Chen ; ^a ; ^{chenwf@fimmu.com}
• 关键词：Sparse angular CT ; POCS ; Non-local means ; Iterative-correction
• 刊名：Computers in Biology and Medicine
• 出版年：2011
• 出版时间：April 2011
• 年：2011
• 卷：41
• 期：4
• 页码：195-205
• 全文大小：1738 K

文摘

In divergent-beam computed tomography (CT), sparse angular sampling frequently leads to conspicuous streak artifacts. In this paper, we propose a novel non-local means (NL-means) based iterative-correction projection onto convex sets (POCS) algorithm, named as NLMIC-POCS, for effective and robust sparse angular CT reconstruction. The motivation for using NLMIC-POCS is that NL-means filtered image can produce an acceptable priori solution for sequential POCS iterative reconstruction. The NLMIC-POCS algorithm has been tested on simulated and real phantom data. The experimental results show that the presented NLMIC-POCS algorithm can significantly improve the image quality of the sparse angular CT reconstruction in suppressing streak artifacts and preserving the edges of the image.