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Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography
Yin, Lin1,2; Wang, Kun1,2; Tong, Tong1,2; An, Yu1,2; Meng, Hui1,2; Yang, Xin1,2; Tian, Jie1,2,3
Source PublicationIEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
ISSN0018-9294
2020-07-01
Volume67Issue:7Pages:2023-2032
Abstract

Objective: Bioluminescence tomography (BLT) is a non-invasive technique designed to enable three-dimensional (3D) visualization and quantification of viable tumor cells in living organisms. However, despite the excellent sensitivity and specificity of bioluminescence imaging (BLI), BLT is limited by the photon scattering effect and ill-posed inverse problem. If the complete structural information of a light source is considered when solving the inverse problem, reconstruction accuracy will be improved. Methods: This article proposed a block sparse Bayesian learning method based on K-nearest neighbor strategy (KNN-BSBL), which incorporated several types of a priori information including sparsity, spatial correlations among neighboring points, and anatomical information to balance over-sparsity and morphology preservation in BLT. Furthermore, we considered the Gaussian weighted distance prior in a light source and proposed a KNN-GBSBL method to further improve the performance of KNN-BSBL. Results: The results of numerical simulations and in vivo glioma-bearing mouse experiments demonstrated that KNN-BSBL and KNN-GBSBL achieved superior accuracy for tumor spatial positioning and morphology reconstruction. Conclusion: The proposed method KNN-BSBL incorporated several types of a priori information is an efficient and robust reconstruction method for BLT.

KeywordImage reconstruction Bayes methods Tumors Inverse problems Light sources Tomography Morphology Bioluminescence tomography (BLT) block sparse Bayesian learning morphology recovery
DOI10.1109/TBME.2019.2953732
WOS KeywordFLUORESCENCE MOLECULAR TOMOGRAPHY ; LIGHT ; OPTIMIZATION ; PROPAGATION ; ALGORITHMS ; RECOVERY ; SIGNALS ; MOUSE
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] ; Ministry of Science and Technology of China[2016YFA0100902] ; National Natural Science Foundation of China[61671449] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[81871442] ; Chinese Academy of Sciences[GJJSTD20170004] ; Chinese Academy of Sciences[KFJ-STS-ZDTP-059] ; Chinese Academy of Sciences[YJKYYQ20180048] ; Chinese Academy of Sciences[QYZDJSSW-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:000544063000020
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/40069
Collection中国科学院分子影像重点实验室
Corresponding AuthorTian, Jie
Affiliation1.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China
First Author AffilicationChinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yin, Lin,Wang, Kun,Tong, Tong,et al. Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2020,67(7):2023-2032.
APA Yin, Lin.,Wang, Kun.,Tong, Tong.,An, Yu.,Meng, Hui.,...&Tian, Jie.(2020).Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,67(7),2023-2032.
MLA Yin, Lin,et al."Improved Block Sparse Bayesian Learning Method Using K-Nearest Neighbor Strategy for Accurate Tumor Morphology Reconstruction in Bioluminescence Tomography".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 67.7(2020):2023-2032.
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