Total variation regularization for bioluminescence tomography with the split Bregman method

被引：38
|
作者：
Feng, Jinchao [1 ]
Qin, Chenghu [2 ]
Jia, Kebin [1 ]
Zhu, Shouping [3 ]
Liu, Kai [2 ]
Han, Dong [2 ]
Yang, Xin [2 ]
Gao, Quansheng [3 ]
Tian, Jie [2 ,4 ]
机构：
[1] Beijing Univ Technol, Coll Elect Informat & Control Engn, Beijing 100124, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Intelligent Med Res Ctr, Beijing 100190, Peoples R China
[3] Acad Mil Med Sci, Lab Anim Ctr, Beijing 100850, Peoples R China
[4] Xidian Univ, Life Sci Res Ctr, Xian 710071, Peoples R China
来源：
APPLIED OPTICS | 2012年 / 51卷 / 19期
基金：
中国国家自然科学基金;
关键词：
TOTAL-VARIATION MINIMIZATION; IMAGE-RECONSTRUCTION; OPTICAL TOMOGRAPHY; SIMULATION; ALGORITHMS; STRATEGY;
D O I：
10.1364/AO.51.004501
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
Regularization methods have been broadly applied to bioluminescence tomography (BLT) to obtain stable solutions, including l(2) and l(1) regularizations. However, l(2) regularization can oversmooth reconstructed images and l(1) regularization may sparsify the source distribution, which degrades image quality. In this paper, the use of total variation (TV) regularization in BLT is investigated. Since a nonnegativity constraint can lead to improved image quality, the nonnegative constraint should be considered in BLT. However, TV regularization with a nonnegativity constraint is extremely difficult to solve due to its nondifferentiability and nonlinearity. The aim of this work is to validate the split Bregman method to minimize the TV regularization problem with a nonnegativity constraint for BLT. The performance of split Bregman-resolved TV (SBRTV) based BLT reconstruction algorithm was verified with numerical and in vivo experiments. Experimental results demonstrate that the SBRTV regularization can provide better regularization quality over l(2) and l(1) regularizations. (c) 2012 Optical Society of America
引用
收藏
页码：4501 / 4512
页数：12
相关论文
共 50 条
  • [1] Lp Regularization for Bioluminescence Tomography Based on the Split Bregman Method
    Hu, Yifang
    Liu, Jie
    Leng, Chengcai
    An, Yu
    Zhang, Shuang
    Wang, Kun
    MOLECULAR IMAGING AND BIOLOGY, 2016, 18 (06) : 830 - 837
  • [2] Lp Regularization for Bioluminescence Tomography Based on the Split Bregman Method
    Yifang Hu
    Jie Liu
    Chengcai Leng
    Yu An
    Shuang Zhang
    Kun Wang
    Molecular Imaging and Biology, 2016, 18 : 830 - 837
  • [3] Total Variation Regularization With Split Bregman-Based Method in Magnetic Induction Tomography Using Experimental Data
    Li, Fang
    Abascal, Juan F. P. J.
    Desco, Manuel
    Soleimani, Manuchehr
    IEEE SENSORS JOURNAL, 2017, 17 (04) : 976 - 985
  • [4] Fast Total Variation Regularization for Higher Resolution in Fluorescence Tomography: A Split Bregman Iteration Approach
    Behrooz, Ali
    Zhou, Hao-Min
    Eftekhar, Ali A.
    Adibi, Ali
    2011 IEEE PHOTONICS CONFERENCE (PHO), 2011, : 725 - +
  • [5] Iterative Reconstruction for Bioluminescence Tomography with Total Variation Regularization
    Jin, Wenma
    He, Yonghong
    OPTICS IN HEALTH CARE AND BIOMEDICAL OPTICS V, 2012, 8553
  • [6] Split Bregman iteration algorithm for total bounded variation regularization based image deblurring
    Liu, Xinwu
    Huang, Lihong
    JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS, 2010, 372 (02) : 486 - 495
  • [7] Total variation regularization for bioluminescence tomography with an adaptive parameter choice approach
    Feng, Jinchao
    Jia, Xiaowei
    Jia, Kebin
    Qin, Chenghu
    Tian, Jie
    2011 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2011, : 3946 - 3949
  • [8] Reweighted Total Variation Regularization Based on Split Bregman in Synthetic Aperture Imaging Radiometry
    Yang, Xiaocheng
    Lu, Chaodong
    Yan, Jingye
    Wu, Lin
    Jiang, Mingfeng
    Li, Lin
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2022, 19
  • [9] Reconstruction Method for In Vivo Bioluminescence Tomography Based on the Split Bregman Iterative and Surrogate Functions
    Shuang Zhang
    Kun Wang
    Hongbo Liu
    Chengcai Leng
    Yuan Gao
    Jie Tian
    Molecular Imaging and Biology, 2017, 19 : 245 - 255
  • [10] Reconstruction Method for In Vivo Bioluminescence Tomography Based on the Split Bregman Iterative and Surrogate Functions
    Zhang, Shuang
    Wang, Kun
    Liu, Hongbo
    Leng, Chengcai
    Gao, Yuan
    Tian, Jie
    MOLECULAR IMAGING AND BIOLOGY, 2017, 19 (02) : 245 - 255
12345