Institutional Repository of Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
Reconstruction for Fluorescence Molecular Tomography via Adaptive Group Orthogonal Matching Pursuit | |
Kong, Lingxin1,2; An, Yu1,2; Liang, Qian1,2; Yin, Lin1,2; Du, Yang1,2; Tian, Jie1,2,3,4 | |
发表期刊 | IEEE Transactions on Biomedical Engineering |
ISSN | 0018-9294 |
2020-01 | |
卷号 | 67期号:10.1109/TBME.2019.2963815页码:1-12 |
通讯作者 | Du, Yang(yang.du@ia.ac.cn) ; Tian, Jie(tian@ieee.org) |
文章类型 | Article |
摘要 | Objective: Fluorescence molecular tomography (FMT) is a promising medical imaging technology aimed at the non-invasive, specific, and sensitive detection of the distribution of fluorophore. Conventional sparsity prior-based methods of FMT commonly face problems such as over-sparseness, spatial discontinuity, and poor robustness, due to the neglect of the interrelation within the local subspace. To address this, we propose an adaptive group orthogonal matching pursuit (AGOMP) method. Methods: AGOMP is based on a novel local spatial-structured sparse regularization, which leverages local spatial interrelations as group sparsity without the hard prior of the tumor region. The adaptive grouped subspace matching pursuit method was adopted to enhance the interrelatedness of elements within a group, which alleviates the over-sparsity problem to some extent and improves the accuracy, robustness, and morphological similarity of FMT reconstruction. A series of numerical simulation experiments, based on digital mouse with both one and several tumors, were conducted, as well as in vivo mouse experiments. Results: The results demonstrated that the proposed AGOMP method achieved better location accuracy, fluorescent yield reconstruction, relative sparsity, and morphology than state-of-the-art methods under complex conditions for levels of Gaussian noise ranging from 5–25%. Furthermore, the in vivo mouse experiments demonstrated the practical application of FMT with AGOMP. Conclusion: The proposed AGOMP can improve the accuracy and robustness for FMT reconstruction in biomedical application. |
关键词 | adaptive group orthogonal matching pursuit fluorescence molecular tomography local spatial structured sparsity regularization inverse problem |
DOI | 10.1109/TBME.2019.2963815 |
关键词[WOS] | LAPLACE PRIOR REGULARIZATION ; LIGHT ; STRATEGY |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Ministry of Science and Technology of China[2017YFA0205] ; National Natural Science Foundation of China[81871514] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81470083] ; National Natural Science Foundation of China[91859119] ; National Natural Science Foundation of China[61671449] ; National Natural Science Foundation of China[81527805] ; National Natural Science Foundation of China[61901472] ; National Public Welfare Basic Scientific Research Program of Chinese Academy of Medical Sciences[2018PT32003] ; National Public Welfare Basic Scientific Research Program of Chinese Academy of Medical Sciences[2017PT32004] ; National Key R&D Program of China[2018YFC0910602] ; National Key R&D Program of China[2017YFA0205200] ; National Key R&D Program of China[2017YFA0700401] ; National Key R&D Program of China[2016YFA0100902] ; National Key R&D Program of China[2016YFC0103702] ; China Postdoctoral Science Foundation[2017M620952] |
项目资助者 | Ministry of Science and Technology of China ; National Natural Science Foundation of China ; National Public Welfare Basic Scientific Research Program of Chinese Academy of Medical Sciences ; National Key R&D Program of China ; China Postdoctoral Science Foundation |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Biomedical |
WOS记录号 | WOS:000562053800012 |
出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
七大方向——子方向分类 | 医学影像处理与分析 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/39021 |
专题 | 中国科学院分子影像重点实验室 |
通讯作者 | Du, Yang; Tian, Jie |
作者单位 | 1.中国科学院自动化研究所 2.中国科学院大学 3.北航大数据精准医学研究中心 4.西电分子与神经影像工程研究中心 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Kong, Lingxin,An, Yu,Liang, Qian,et al. Reconstruction for Fluorescence Molecular Tomography via Adaptive Group Orthogonal Matching Pursuit[J]. IEEE Transactions on Biomedical Engineering,2020,67(10.1109/TBME.2019.2963815):1-12. |
APA | Kong, Lingxin,An, Yu,Liang, Qian,Yin, Lin,Du, Yang,&Tian, Jie.(2020).Reconstruction for Fluorescence Molecular Tomography via Adaptive Group Orthogonal Matching Pursuit.IEEE Transactions on Biomedical Engineering,67(10.1109/TBME.2019.2963815),1-12. |
MLA | Kong, Lingxin,et al."Reconstruction for Fluorescence Molecular Tomography via Adaptive Group Orthogonal Matching Pursuit".IEEE Transactions on Biomedical Engineering 67.10.1109/TBME.2019.2963815(2020):1-12. |
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