Fast Total Variation Regularization for Higher Resolution in Fluorescence Tomography: A Split Bregman Iteration Approach

被引：0

作者：

Behrooz, Ali ^{[1
]}

Zhou, Hao-Min ^{[2
]}

Eftekhar, Ali A. ^{[1
]}

Adibi, Ali ^{[1
]}

机构：

[1] Georgia Inst Technol, Sch Elect & Comp Engn, 777 Atlantic Dr, Atlanta, GA 30332 USA

[2] Sch Math, Georgia Inst Technol, Atlanta, GA 30332 USA

来源：

2011 IEEE PHOTONICS CONFERENCE (PHO) | 2011年

关键词：

Medical imaging; fluorescence tomography; optical tomography; molecular imaging; in-vivo imaging;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We present an edge-preserving regularization for fluorescence tomography that improves its resolution and noise robustness through penalizing the total variation (TV) norm of the reconstructed fluorescent distribution. Results are validated by numerical and phantom-based studies.

引用

页码：725 / +

页数：2