DocumentCode :
27439
Title :
Adaptive monotone fast iterative shrinkage thresholding algorithm for fluorescence molecular tomography
Author :
Erxi Fang ; Jiajun Wang ; Danfeng Hu ; Jingya Zhang ; Wei Zou ; Yue Zhou
Author_Institution :
Sch. of Electron. & Inf. Eng., Soochow Univ., Suzhou, China
Volume :
9
Issue :
5
fYear :
2015
fDate :
8 2015
Firstpage :
587
Lastpage :
595
Abstract :
Fluorescence molecular tomography is an ill-posed inverse problem. Considering the sparsity of the fluorescent source, authors proposed to alleviate this problem by including the L1-norm regularisation term in the objective function. To obtain a solution to such an optimisation problem, an innovative version of the traditional over-relaxation algorithm was proposed by including additional procedures for updating the step size and the regularisation parameter adaptively. Simulation results demonstrate that our proposed algorithm can improve the reconstruction accuracy and convergence speed effectively as compared with existed algorithms such as the perturbation algorithm and the over-relaxation algorithm.
Keywords :
adaptive estimation; biological techniques; biological tissues; fluorescence; image reconstruction; inverse problems; iterative methods; optical tomography; optimisation; FMT reconstruction problem; L1-norm regularisation; adaptive monotone fast iterative shrinkage thresholding algorithm; fluorescence molecular tomography; fluorescent source; ill-posed inverse problem; optimisation problem; over-relaxation algorithm; step size;
fLanguage :
English
Journal_Title :
Science, Measurement & Technology, IET
Publisher :
iet
ISSN :
1751-8822
Type :
jour
DOI :
10.1049/iet-smt.2014.0030
Filename :
7172606
Link To Document :
بازگشت