Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Bioluminescence tomography based on Bayesian approach | |
Feng, Jinchao; Jia, Kebin; Tian, Jie; Yan, Guorui; Qin, Chenghu | |
2009 | |
会议名称 | Progress in Biomedical Optics and Imaging - SPIE |
会议录名称 | Progress in Biomedical Optics and Imaging - SPIE |
会议日期 | 2009 |
会议地点 | United States San Diego |
摘要 | As a new mode of molecular imaging, bioluminescence tomography (BLT) will have significant effect on revealing the molecular and cellular information in vivo at the whole-body small animal level because of its high sensitive detection and facile operation. However, BLT is an ill-posed problem, it is necessary to incorporate a priori knowledge into the tomographic algorithm. In this paper, a novel Bayesian reconstruction algorithm for BLT is firstly proposed. In the algorithm, a priori permissible source region strategy is incorporated into the Bayesian network to reduce the ill-posedness of BLT. Then a generalized adaptive Gaussian Markov random field (GAGMRF) prior model for unknown source density estimation is developed to further reduce the ill-posedness of BLT on the basis of adaptive finite element analysis. Finally, the algorithm maximizes the log posterior probability with respect to a noise parameter and the unknown source density, the distribution of bioluminescent source can be reconstructed. In addition, the novel tomography algorithm based adaptive finite element makes the method more appropriate for complex phantom such as real mouse. In the numerical simulation, a heterogeneousphantom is used to evaluate the performance of the proposed algorithm with the Monte Carlo basedsynthetic data. The accurate localization of bioluminescent source and quantitative results show the effectiveness and potential of the tomographic algorithm for BLT. |
关键词 | Bioluminescence Tomography Bayesian Approach Generalized Adaptive Gaussian Markov Random Field Light Source Reconstruction Diffusion Approximation Adaptive Finite Element Method Monte Carlo Methods |
收录类别 | EI |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/5424 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Tian, Jie |
推荐引用方式 GB/T 7714 | Feng, Jinchao,Jia, Kebin,Tian, Jie,et al. Bioluminescence tomography based on Bayesian approach[C],2009. |
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