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Proceedings Paper

A novel reconstruction algorithm for bioluminescent tomography based on Bayesian compressive sensing
Author(s): Yaqi Wang; Jinchao Feng; Kebin Jia; Zhonghua Sun; Huijun Wei
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Paper Abstract

Bioluminescence tomography (BLT) is becoming a promising tool because it can resolve the biodistribution of bioluminescent reporters associated with cellular and subcellular function through several millimeters with to centimeters of tissues in vivo. However, BLT reconstruction is an ill-posed problem. By incorporating sparse a priori information about bioluminescent source, enhanced image quality is obtained for sparsity based reconstruction algorithm. Therefore, sparsity based BLT reconstruction algorithm has a great potential. Here, we proposed a novel reconstruction method based on Bayesian compressive sensing and investigated its feasibility and effectiveness with a heterogeneous phantom. The results demonstrate the potential and merits of the proposed algorithm.

Paper Details

Date Published: 29 March 2016
PDF: 6 pages
Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97880T (29 March 2016); doi: 10.1117/12.2216564
Show Author Affiliations
Yaqi Wang, Beijing Univ. of Technology (China)
Jinchao Feng, Beijing Univ. of Technology (China)
Kebin Jia, Beijing Univ. of Technology (China)
Zhonghua Sun, Beijing Univ. of Technology (China)
Huijun Wei, Beijing Univ. of Technology (China)


Published in SPIE Proceedings Vol. 9788:
Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

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