CASIA OpenIR  > 中国科学院分子影像重点实验室
Robust reconstruction of fluorescence molecular tomography based on correntropy matching pursuit method for stem cell tracing
Ma XB(马喜波)
Source PublicationIEEE transactions on medical imaging
2018-10
Volume37Issue:10Pages:2176-2184
AbstractFluorescence molecular tomography, as a promising imaging modality in preclinical research, can obtain the three-dimensional 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 chanlenge to develop a robust reconstruction method, which can accurately locate the stem cells and define the distribution. In this study, we proposed a sparsity adaptive correntropy matching pursuit (SACMP) method. SACMP method is independent on the noise distribution of measurements and it assign small weights on severely corrupted entries of data and large weights on severely corrupted entries of data and large weights on clean ones adaptively.
KeywordFluorescence Molecular tomography+inverse problem+sparsity Adaptive Correntropy Matching pursuit+robust Reconstruction
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21741
Collection中国科学院分子影像重点实验室
Recommended Citation
GB/T 7714
Ma XB. Robust reconstruction of fluorescence molecular tomography based on correntropy matching pursuit method for stem cell tracing[J]. IEEE transactions on medical imaging,2018,37(10):2176-2184.
APA Ma XB.(2018).Robust reconstruction of fluorescence molecular tomography based on correntropy matching pursuit method for stem cell tracing.IEEE transactions on medical imaging,37(10),2176-2184.
MLA Ma XB."Robust reconstruction of fluorescence molecular tomography based on correntropy matching pursuit method for stem cell tracing".IEEE transactions on medical imaging 37.10(2018):2176-2184.
Files in This Item: Download All
File Name/Size DocType Version Access License
TMI-2018-正式版.pdf(1623KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Ma XB(马喜波)]'s Articles
Baidu academic
Similar articles in Baidu academic
[Ma XB(马喜波)]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Ma XB(马喜波)]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: TMI-2018-正式版.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.