CASIA OpenIR  > 中国科学院分子影像重点实验室
Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography
Yin, Lin; Wang, Kun; Tong, Tong; Wang, Qian; An, Yu; Yang, Xin; Tian, Jie
Source PublicationIEEE Transactions on Biomedical Engineering
ISSN0018-9294
2021
Volume68Issue:99Pages:1
SubtypeSCI
Abstract

Objective: Bioluminescence tomography (BLT) is a promising modality that is designed to provide non-invasive quantitative three-dimensional information regarding the tumor distribution in living animals. However, BLT suffers from inferior reconstructions due to its ill-posedness. This study aims to improve the reconstruction performance of BLT. Methods: We propose an adaptive grouping block sparse Bayesian learning (AGBSBL) method, which incorporates the sparsity prior, correlation of neighboring mesh nodes, and anatomical structure prior to balance the sparsity and morphology in BLT. Specifically, an adaptive grouping prior model is proposed to adjust the grouping according to the intensity of the mesh nodes during the optimization process. Results: Numerical simulations and in vivo experiments demonstrate that AGBSBL yields a high position and morphology recovery accuracy, stability, and practicality. Conclusion: The proposed method is a robust and effective reconstruction algorithm for BLT. Moreover, the proposed adaptive grouping strategy can further increase the practicality of BLT in biomedical applications.

Keywordadaptive grouping bioluminescence tomography block sparse Bayesian learning
DOI10.1109/TBME.2021.3071823
WOS KeywordLAPLACE PRIOR REGULARIZATION ; MOUSE ; LIGHT ; REGISTRATION ; PROPAGATION ; ALGORITHMS ; SIMULATION
Indexed BySCI
Language英语
Funding ProjectMinistry of Science and Technology of China[2017YFA0205200] ; Ministry of Science and Technology of China[2017YFA0700401] ; Ministry of Science and Technology of China[2016YFC0103803] ; National Natural Science Foundation of China[61671449] ; National Natural Science Foundation of China[61901472] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Chinese Academy of Sciences[YJKYYQ20180048] ; Chinese Academy of Sciences[QYZDJ-SSW-JSC005] ; Chinese Academy of Sciences[XDBS01030200]
Funding OrganizationMinistry of Science and Technology of China ; National Natural Science Foundation of China ; Chinese Academy of Sciences
WOS Research AreaEngineering
WOS SubjectEngineering, Biomedical
WOS IDWOS:000709080500024
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/44354
Collection中国科学院分子影像重点实验室
Corresponding AuthorWang, Kun; Tian, Jie
Affiliation1.the CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences
2.School of Artificial Intelligence, University of Chinese Academy of Sciences
3.Department of Diagnostic Imaging, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
4.Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing
Recommended Citation
GB/T 7714
Yin, Lin,Wang, Kun,Tong, Tong,et al. Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography[J]. IEEE Transactions on Biomedical Engineering,2021,68(99):1.
APA Yin, Lin.,Wang, Kun.,Tong, Tong.,Wang, Qian.,An, Yu.,...&Tian, Jie.(2021).Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography.IEEE Transactions on Biomedical Engineering,68(99),1.
MLA Yin, Lin,et al."Adaptive Grouping Block Sparse Bayesian Learning Method for Accurate and Robust Reconstruction in Bioluminescence Tomography".IEEE Transactions on Biomedical Engineering 68.99(2021):1.
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