UM  > 健康科學學院
Comparison of regularization methods in fluorescence molecular tomography
Zhu D.1; Zhao Y.1; Baikejiang R.1; Yuan Z.2; Li C.1
2014-06-01
Source PublicationPhotonics
ISSN23046732
Volume1Issue:2Pages:95-109
AbstractIn vivo fluorescence molecular tomography (FMT) has been a popular functional imaging modality in research labs in the past two decades. One of the major difficulties of FMT lies in the ill-posed and ill-conditioned nature of the inverse problem in reconstructing the distribution of fluorophores inside objects. The popular regularization methods based on L, L and total variation (TV) norms have been applied in FMT reconstructions. The non-convex L(0 < q < 1) semi-norm and Log function have also been studied recently. In this paper, we adopt a uniform optimization transfer framework for these regularization methods in FMT and compare their individual, as well as the combined effects on both small, localized targets, such as tumors in the early stage, and large targets, such as liver. Numerical simulation studies and phantom experiments have been carried out, and we found that L with q near 1/2 performs the best in reconstructing small targets, while joint L and Log performs the best for large targets.
KeywordFluorescence molecular tomography Optics Optimization transfer Reconstruction techniques
DOI10.3390/photonics1020095
URLView the original
Language英語
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionFaculty of Health Sciences
Affiliation1.UC Merced
2.Universidade de Macau
Recommended Citation
GB/T 7714
Zhu D.,Zhao Y.,Baikejiang R.,et al. Comparison of regularization methods in fluorescence molecular tomography[J]. Photonics,2014,1(2):95-109.
APA Zhu D.,Zhao Y.,Baikejiang R.,Yuan Z.,&Li C..(2014).Comparison of regularization methods in fluorescence molecular tomography.Photonics,1(2),95-109.
MLA Zhu D.,et al."Comparison of regularization methods in fluorescence molecular tomography".Photonics 1.2(2014):95-109.
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Zhu D.]'s Articles
[Zhao Y.]'s Articles
[Baikejiang R.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Zhu D.]'s Articles
[Zhao Y.]'s Articles
[Baikejiang R.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Zhu D.]'s Articles
[Zhao Y.]'s Articles
[Baikejiang R.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

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