Sparse reconstruction for fluorescence molecular tomography via a fast iterative algorithm
Sparse reconstruction for fluorescence molecular tomography via a fast iterative algorithm
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通过快速迭代算法进行荧光分子断层扫描的稀疏重建
DOI：
10.1142/s1793545814500084
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发表时间：
2014-05
影响因子：
2.5
通讯作者：
He Xiaowei
中科院分区：
文献类型：
--
作者：
Yu Jingjing;Cheng Jingxing;Hou Yuqing;He Xiaowei
Fluorescence molecular tomography (FMT) is a fast-developing optical imaging modality that has great potential in early diagnosis of disease and drugs development. However, reconstruction algorithms have to address a highly ill-posed problem to fulfill 3D reconstruction in FMT. In this contribution, we propose an efficient iterative algorithm to solve the large-scale reconstruction problem, in which the sparsity of fluorescent targets is taken as useful a priori information in designing the reconstruction algorithm. In the implementation, a fast sparse approximation scheme combined with a stage-wise learning strategy enable the algorithm to deal with the ill-posed inverse problem at reduced computational costs. We validate the proposed fast iterative method with numerical simulation on a digital mouse model. Experimental results demonstrate that our method is robust for different finite element meshes and different Poisson noise levels.
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