Adaptive monotone fast iterative shrinkage thresholding algorithm for fluorescence molecular tomography

摘要

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.