DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ahn, Hyun-Seo | ko |
dc.contributor.author | Park, Sung-Hong | ko |
dc.contributor.author | Ye, Jong Chul | ko |
dc.date.accessioned | 2019-12-20T06:20:07Z | - |
dc.date.available | 2019-12-20T06:20:07Z | - |
dc.date.created | 2019-09-24 | - |
dc.date.created | 2019-09-24 | - |
dc.date.created | 2019-09-24 | - |
dc.date.created | 2019-09-24 | - |
dc.date.created | 2019-09-24 | - |
dc.date.issued | 2020-03 | - |
dc.identifier.citation | MAGNETIC RESONANCE IN MEDICINE, v.83, no.3, pp.858 - 871 | - |
dc.identifier.issn | 0740-3194 | - |
dc.identifier.uri | http://hdl.handle.net/10203/270006 | - |
dc.description.abstract | Purpose Quantitative susceptibility mapping (QSM) inevitably suffers from streaking artifacts caused by zeros on the conical surface of the dipole kernel in k-space. This work proposes a novel and accurate QSM reconstruction method based on k-space low-rank Hankel matrix constraint, avoiding the over-smoothing problem and streaking artifacts. Theory and Methods Based on the recent theory of annihilating filter-based low-rank Hankel matrix approach (ALOHA), QSM is formulated as deconvolution under low-rank Hankel matrix constraint in the k-space. The computational complexity and the high memory burden were reduced by successive reconstruction of 2-D planes along 3 independent axes of the 3-D phase image in Fourier domain. Feasibility of the proposed method was tested on a simulated phantom and human data and were compared with existing QSM reconstruction methods. Results The proposed ALOHA-QSM effectively reduced streaking artifacts and accurately estimated susceptibility values in deep gray matter structures, compared to the existing QSM methods. Conclusions The suggested ALOHA-QSM algorithm successfully solves the 3-dimensional QSM dipole inversion problem using k-space low rank property with no anatomical constraint. ALOHA-QSM can provide detailed brain structures and accurate susceptibility values with no streaking artifacts. | - |
dc.language | English | - |
dc.publisher | WILEY | - |
dc.title | Quantitative susceptibility map reconstruction using annihilating filter-based low-rank Hankel matrix approach | - |
dc.type | Article | - |
dc.identifier.wosid | 000484203700001 | - |
dc.identifier.scopusid | 2-s2.0-85071387087 | - |
dc.type.rims | ART | - |
dc.citation.volume | 83 | - |
dc.citation.issue | 3 | - |
dc.citation.beginningpage | 858 | - |
dc.citation.endingpage | 871 | - |
dc.citation.publicationname | MAGNETIC RESONANCE IN MEDICINE | - |
dc.identifier.doi | 10.1002/mrm.27976 | - |
dc.contributor.localauthor | Park, Sung-Hong | - |
dc.contributor.localauthor | Ye, Jong Chul | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | dipole inversion | - |
dc.subject.keywordAuthor | low-rank Hankel matrix completion | - |
dc.subject.keywordAuthor | quantitative susceptibility mapping | - |
dc.subject.keywordPlus | PIECEWISE-CONSTANT IMAGES | - |
dc.subject.keywordPlus | ENABLED DIPOLE INVERSION | - |
dc.subject.keywordPlus | K-SPACE NEIGHBORHOODS | - |
dc.subject.keywordPlus | MAGNETIC-FIELD | - |
dc.subject.keywordPlus | SPATIAL VARIATION | - |
dc.subject.keywordPlus | RECOVERY | - |
dc.subject.keywordPlus | LORAKS | - |
dc.subject.keywordPlus | INHOMOGENEITY | - |
dc.subject.keywordPlus | CONSISTENCY | - |
dc.subject.keywordPlus | ALGORITHM | - |
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