A novel reconstruction algorithm for bioluminescent tomography based on Bayesian compressive sensing

Yaqi Wang; Jinchao Feng; Kebin Jia; Zhonghua Sun; Huijun Wei

doi:10.1117/12.2216564

29 March 2016 A novel reconstruction algorithm for bioluminescent tomography based on Bayesian compressive sensing

Yaqi Wang, Jinchao Feng, Kebin Jia, Zhonghua Sun, Huijun Wei

Author Affiliations +

Proceedings Volume 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging; 97880T (2016) https://doi.org/10.1117/12.2216564
Event: SPIE Medical Imaging, 2016, San Diego, California, United States

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.

Citation Download Citation

Yaqi Wang, Jinchao Feng, Kebin Jia, Zhonghua Sun, and Huijun Wei "A novel reconstruction algorithm for bioluminescent tomography based on Bayesian compressive sensing", Proc. SPIE 9788, Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, 97880T (29 March 2016); https://doi.org/10.1117/12.2216564

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