Open AccessAdaptive monotone fast iterative shrinkage thresholding algorithm for fluorescence molecular tomography
Author(s) -
Fang Erxi,
Wang Jiajun,
Hu Danfeng,
Zhang Jingya,
Zou Wei,
Zhou Yue
Publication year - 2015
Publication title -
iet science, measurement and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.418
H-Index - 49
eISSN - 1751-8830
pISSN - 1751-8822
DOI - 10.1049/iet-smt.2014.0030
Subject(s) - algorithm , inverse problem , thresholding , convergence (economics) , relaxation (psychology) , monotone polygon , mathematical optimization , computer science , perturbation (astronomy) , norm (philosophy) , iterative method , mathematics , artificial intelligence , psychology , mathematical analysis , social psychology , physics , geometry , quantum mechanics , political science , law , economics , image (mathematics) , economic growth
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.