Sparse reconstruction for fluorescence molecular tomography via a fast iterative algorithm

作     者：Jingjing Yu Jingxing Cheng Yuqing Hou Xiaowei He 

作者机构：School of Physics and Information Technology Shaanai Normal UniversityXian 710062P.R.China School of Information Sciences and Technology Northwest UniversityXi'an 710069P.R.China 

出 版 物：《Journal of Innovative Optical Health Sciences》 (创新光学健康科学杂志（英文）)

年 卷 期：2014年第7卷第3期

页      面：50-58页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 1004[医学-公共卫生与预防医学(可授医学、理学学位)] 0808[工学-电气工程] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 0805[工学-材料科学与工程（可授工学、理学学位）] 0836[工学-生物工程] 0701[理学-数学] 0702[理学-物理学] 

基　　金：supported by the National Natural Science Foundation of China(Grant No.61372046) the Research Fund for the Doctoral Program ofHigher Education of China(New Teachers)(Grant No.20116101120018) the China Postdoctoral Sci-ence_Foundation_Funded Project(Grant_Nos.2011M501467 and 2012T50814) the Natural Sci-ence Basic Research Plan in Shaanxi Province of China(Grant No.2011JQ1006) the Fund amental Research Funds for the Central Universities(Grant No.GK201302007) Science and Technology Plan Program in Shaanxi Province of China(Grant Nos.2012 KJXX-29 and 2013K12-20-12) the Scienceand Technology Plan Program in Xi'an of China(Grant No.CXY 1348(2)). 

主　　题：Fluorescence molecular tomography sparse regularization reconstruction algorithm least absolute shrinkage and selection operator. 

摘      要：Fluorescence molecular tomography(FMT)is a fast-developing optical imaging modalitythat has great potential in early diagnosis of disease and drugs development.However,recon-struction algorithms have to address a highly ill-posed problem to fulfll 3D reconstruction inFMT.In this contribution,we propose an efficient iterative algorithm to solve the large-scalereconstruction problem,in which the sparsity of fluorescent targets is taken as useful a prioriinformation in designing the reconstruction algorithm.In the implementation,a fast sparseapproximation scheme combined with a stage-wise learning strategy enable the algorithm to dealwith the ill-posed inverse problem at reduced computational costs.We validate the proposed fastiterative method with numerical simulation on a digital mouse model.Experimental results demonstrate that our method is robust for different finite element meshes and different Poissonnoise levels.