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A fast reconstruction algorithm for fluorescence molecular tomography via multipath subspace pursuit method
Author(s): HaoXuan Ni; Jinzuo Ye; Dehui Xiang; Yang Du; Xinjian Chen; Xiang Deihui; Jie Tian
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Paper Abstract

Fluorescence Molecular Tomography (FMT) is one of the most important preclinical research techniques, which can obtain three-dimensional reconstruction of tumors in mouse in vivo. However, the ill-posedness of FMT makes its reconstruction a challenging problem. Therefore, more effective, robust, and accurate reconstruction methods are needed to be developed to solve the FMT reconstruction problem.

In this paper, a reconstruction method named multipath subspace pursuit (MSP) is applied to solve the FMT problem. At the end of an iteration, the MSP method creates several candidate support set. Through evaluating the normal of final residual vector, the best candidate can be selected as the final support set. Then the support set is used for reconstructing sense matrix to achieve the goal of FMT reconstruction.

In order to verity the reconstruction result of the proposed MSP method, the simulated experiment of triple fluorescent sources and quantitative analyses of position error and relative intensity error for the experiment have been conducted. The MSP method obtains satisfactory results, and the source position error is below 1 mm. Moreover, the computation time of the MSP method is about one order of magnitude less than iterated shrinkage with the L1-norm (IS_L1) method. The MSP method not only can obtain the result of robustness but also can reduce the artifacts in the background. The above results revealed the MSP method for the potential FMT application.

Paper Details

Date Published: 12 March 2018
PDF: 8 pages
Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 1057810 (12 March 2018); doi: 10.1117/12.2292280
Show Author Affiliations
HaoXuan Ni, Soochow Univ. (China)
Institute of Automation (China)
Jinzuo Ye, Institute of Automation (China)
Dehui Xiang, Soochow Univ. (China)
Yang Du, Institute of Automation (China)
Univ. of Chinese Academy of Sciences (China)
Xinjian Chen, Soochow Univ. (China)
Xiang Deihui, Soochow Univ. (China)
Jie Tian, Institute of Automation (China)
Univ. of Chinese of Academy of Sciences (China)

Published in SPIE Proceedings Vol. 10578:
Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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