CASIA OpenIR  > 中国科学院分子影像重点实验室
Robust Reconstruction of Fluorescence Molecular Tomography Based on Sparsity Adaptive Correntropy Matching Pursuit Method for Stem Cell Distribution
Zhang, Shuai1,2; Ma, Xibo3,4,5,6; Wang, Yi7; Wu, Meng8; Meng, Hui3,4,5,6; Chai, Wei7; Wang, Xiaojie8; Wei, Shoushui1; Tian, Jie3,4,5,6
Source PublicationIEEE TRANSACTIONS ON MEDICAL IMAGING
ISSN0278-0062
2018-10-01
Volume37Issue:10Pages:2176-2184
Abstract

Fluorescence molecular tomography (FMT), as a promising imaging modality in preclinical research, can obtain the three-dimensional (3-D) position information of the stem cell in mice. However, because of the ill-posed nature and sensitivity to noise of the inverse problem, it is a challenge to develop a robust reconstruction method, which can accurately locate the stem cells and define the distribution. In this paper, we proposed a sparsity adaptive correntropy matching pursuit (SACMP) method. SACMP method is independent on the noise distribution of measurements and it assigns small weights on severely corrupted entries of data and large weights on clean ones adaptively. These properties make it more suitable for in vivo experiment. To analyze the performance in terms of robustness and practicability of SACMP, we conducted numerical simulation and in vivo mice experiments. The results demonstrated that the SACMP method obtained the highest robustness and accuracy in locating stem cells and depicting stem cell distribution compared with stagewise orthogonal matching pursuit and sparsity adaptive subspace pursuit reconstruction methods. To the best of our knowledge, this is the first study that acquired such accurate and robust FMT distribution reconstruction for stem cell tracking in mice brain. This promotes the application of FMT in locating stem cell and distribution reconstruction in practical mice brain injury models.

KeywordFluorescence molecular tomography inverse problem sparsity adaptive correntropy matching pursuit robust reconstruction
DOI10.1109/TMI.2018.2825102
WOS KeywordDIFFUSE OPTICAL TOMOGRAPHY ; IMAGE RECOVERY ; REGULARIZATION ; ALGORITHM ; MAXIMIZATION ; TRACKING ; SIGNAL
Indexed BySCI
Language英语
Funding ProjectScientific Research and Equipment Development Project of Chinese Academy of Sciences[YZ201457] ; National Natural Science Foundation of China[81770781] ; National Natural Science Foundation of China[81472594] ; National Natural Science Foundation of China[81471739] ; National Natural Science Foundation of China[815270805] ; National Key Research Program of China[2017YFA0205200] ; National Key Research Program of China[2016YFA0100902] ; National Key Research Program of China[2016YFA0100900] ; National Natural Science Foundation of China[61231004] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[81227901] ; National Natural Science Foundation of China[61231004] ; National Key Research Program of China[2016YFA0100900] ; National Key Research Program of China[2016YFA0100902] ; National Key Research Program of China[2017YFA0205200] ; National Natural Science Foundation of China[815270805] ; National Natural Science Foundation of China[81471739] ; National Natural Science Foundation of China[81472594] ; National Natural Science Foundation of China[81770781] ; Scientific Research and Equipment Development Project of Chinese Academy of Sciences[YZ201457]
WOS Research AreaComputer Science ; Engineering ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology ; Radiology, Nuclear Medicine & Medical Imaging
WOS IDWOS:000446342100002
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/28112
Collection中国科学院分子影像重点实验室
Corresponding AuthorMa, Xibo; Wei, Shoushui; Tian, Jie
Affiliation1.Shandong Univ, Inst Biomed Engn, Sch Control Sci & Engn, Jinan 250061, Shandong, Peoples R China
2.Chinese Acad Sci, Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
3.Inst Automat, CAS Key Lab Mol Imaging, Beijing 100190, Peoples R China
4.Beijing Key Lab Mol Imaging, Beijing 100190, Peoples R China
5.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
6.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
7.Chinese Peoples Liberat Army Gen Hosp, Med Coll PLA, Beijing 100853, Peoples R China
8.Ludong Univ, Sch Life Sci, Yantai 264001, 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;  Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Zhang, Shuai,Ma, Xibo,Wang, Yi,et al. Robust Reconstruction of Fluorescence Molecular Tomography Based on Sparsity Adaptive Correntropy Matching Pursuit Method for Stem Cell Distribution[J]. IEEE TRANSACTIONS ON MEDICAL IMAGING,2018,37(10):2176-2184.
APA Zhang, Shuai.,Ma, Xibo.,Wang, Yi.,Wu, Meng.,Meng, Hui.,...&Tian, Jie.(2018).Robust Reconstruction of Fluorescence Molecular Tomography Based on Sparsity Adaptive Correntropy Matching Pursuit Method for Stem Cell Distribution.IEEE TRANSACTIONS ON MEDICAL IMAGING,37(10),2176-2184.
MLA Zhang, Shuai,et al."Robust Reconstruction of Fluorescence Molecular Tomography Based on Sparsity Adaptive Correntropy Matching Pursuit Method for Stem Cell Distribution".IEEE TRANSACTIONS ON MEDICAL IMAGING 37.10(2018):2176-2184.
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