Fast Source Reconstruction for Bioluminescence Tomography Based on Sparse Regularization

被引:25
|
作者
Yu, Jingjing [1 ,2 ]
Liu, Fang [1 ,2 ]
Wu, Jiao [1 ,2 ]
Jiao, Licheng [2 ,3 ]
He, Xiaowei [3 ]
机构
[1] Xidian Univ, Sch Comp Sci & Technol, Minist Educ China, Xian 710071, Peoples R China
[2] Xidian Univ, Key Lab Intelligent Percept & Image Understanding, Minist Educ China, Xian 710071, Peoples R China
[3] Xidian Univ, Sch Elect Engn, Minist Educ China, Xian 710071, Peoples R China
基金
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词
Bioluminescence tomography (BLT); least absolute shrinkage and selection operator (LASSO); reconstruction algorithm; sparse regularization; LIGHT;
D O I
10.1109/TBME.2010.2059024
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Bioluminescence tomography (BLT) is an inherent ill-posed inverse problem to reconstruct the internal source in 3-D with limited measurements on the external surface. In most BLT studies so far, a relatively small permissible source region or multispectral approach is typically used to enhance the stability or quality of the solution. In this letter, considering the sparsity characteristic of the light source, BLT is reformulated as a least absolute shrinkage and selection operator (LASSO) problem with l(1) regularization, and then, a fast reconstruction algorithm named as stagewise fast LASSO is proposed for solving this problem. Numerical simulations of a 3-D mouse atlas under different noise levels demonstrate that the proposed algorithm is robust against measurement noise, and it can achieve high computational efficiency and accurate localization of source even without any permissible region constraint.
引用
收藏
页码:2583 / 2586
页数:4
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