Dynamic 3D PET reconstruction for kinetic analysis using patch-based low-rank penalty
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, K.S. | - |
dc.contributor.author | Son, Y.D. | - |
dc.contributor.author | Cho, Z.H. | - |
dc.contributor.author | Ra, J.B. | - |
dc.contributor.author | Ye, J.C. | - |
dc.date.available | 2020-02-29T09:45:25Z | - |
dc.date.created | 2020-02-11 | - |
dc.date.issued | 2012-11 | - |
dc.identifier.issn | 1095-7863 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17507 | - |
dc.description.abstract | Dynamic positron emission tomography (PET) is widely used to identify metabolism over time. However, conventional reconstruction algorithm provides a noisy reconstruction due to the lack of photon counts in each frame. Therefore, the main goal of this paper is to develop a novel spatio-temporal regularization approach that exploits inherent similarities within intra- and inter- frames. One of the main contributions of this paper is to demonstrate that such correlations can be exploited using a low rank constraint of overlapping similarity blocks. The resulting optimization framework is, however, non-smooth and non Lipschitz due to the low-rank penalty terms and Poisson log-likelihood. Therefore, we propose a novel globally convergent optimization method using the concave-convex procedure (CCCP) by exploiting Legendre-Fenchel transform. We confirm that the proposed algorithm can provide significantly improved image quality. © 2012 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE | - |
dc.relation.isPartOf | IEEE Nuclear Science Symposium Conference Record | - |
dc.title | Dynamic 3D PET reconstruction for kinetic analysis using patch-based low-rank penalty | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.1109/NSSMIC.2012.6551782 | - |
dc.identifier.bibliographicCitation | IEEE Nuclear Science Symposium Conference Record, pp.3430 - 3433 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-84881590037 | - |
dc.citation.endPage | 3433 | - |
dc.citation.startPage | 3430 | - |
dc.citation.title | IEEE Nuclear Science Symposium Conference Record | - |
dc.contributor.affiliatedAuthor | Son, Y.D. | - |
dc.contributor.affiliatedAuthor | Cho, Z.H. | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordPlus | Concave-convex procedure | - |
dc.subject.keywordPlus | Globally convergent | - |
dc.subject.keywordPlus | Legendre-Fenchel transforms | - |
dc.subject.keywordPlus | Optimization framework | - |
dc.subject.keywordPlus | Optimization method | - |
dc.subject.keywordPlus | Positron emission tomography (PET) | - |
dc.subject.keywordPlus | Reconstruction algorithms | - |
dc.subject.keywordPlus | Spatio-temporal regularizations | - |
dc.subject.keywordPlus | Algorithms | - |
dc.subject.keywordPlus | Medical imaging | - |
dc.subject.keywordPlus | Nuclear physics | - |
dc.subject.keywordPlus | Positron emission tomography | - |
dc.description.journalRegisteredClass | scopus | - |
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