Effective fat quantification using improved least-square fit at high-field MRI
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Eun, S.-J. | - |
dc.contributor.author | Whangbo, T.-K. | - |
dc.date.available | 2020-02-28T18:46:24Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2014 | - |
dc.identifier.issn | 0000-0000 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/13083 | - |
dc.description.abstract | In high-field magnetic resonance imaging (MRI), water-fat separation in the presence of B0 field inhomogeneity is important research. Various field map estimation techniques that use three-point multi-echo acquisitions have been developed for reliable water fat separation. Among the numerous techniques, iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) has gained considerable popularity as an iterative method for acquiring high-quality water and fat images. However, due to the worsened B0 inhomogeneity at high-field, IDEAL cannot adjust for meaningful field map estimation, particularly for a large field of view. Previously, to improve the robustness of this estimation, a region-growing (RG) technique was developed to take advantage of the 2D linear extrapolation procedure through the seed point set by the median value in the target object. There are some limitations with this approach, such as the dependence on the initial seed point, such as a number, intensity, and position of the seed point. In this work, we introduce a effective method called the improved least square fit method that does not need to consider parameters related with accuracy. As a result of the proposed method, we obtained a effective fat quantification result that can be applied in high-fields, with an average water residual rate of 7.2% higher than the existing method. © 2014 IEEE. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE Computer Society | - |
dc.relation.isPartOf | ICISA 2014 - 2014 5th International Conference on Information Science and Applications | - |
dc.subject | Information science | - |
dc.subject | Magnetic resonance imaging | - |
dc.subject | Fat quantification | - |
dc.subject | Field map estimations | - |
dc.subject | Field map unwrapping | - |
dc.subject | MR images | - |
dc.subject | Region growing | - |
dc.subject | Iterative methods | - |
dc.title | Effective fat quantification using improved least-square fit at high-field MRI | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.1109/ICISA.2014.6847391 | - |
dc.identifier.bibliographicCitation | ICISA 2014 - 2014 5th International Conference on Information Science and Applications | - |
dc.identifier.scopusid | 2-s2.0-84904490417 | - |
dc.citation.title | ICISA 2014 - 2014 5th International Conference on Information Science and Applications | - |
dc.contributor.affiliatedAuthor | Eun, S.-J. | - |
dc.contributor.affiliatedAuthor | Whangbo, T.-K. | - |
dc.type.docType | Conference Paper | - |
dc.subject.keywordAuthor | component | - |
dc.subject.keywordAuthor | MR image | - |
dc.subject.keywordAuthor | Fat quantification | - |
dc.subject.keywordAuthor | Field map estimation | - |
dc.subject.keywordAuthor | Field map unwrapping | - |
dc.subject.keywordAuthor | region growing | - |
dc.subject.keywordPlus | Information science | - |
dc.subject.keywordPlus | Magnetic resonance imaging | - |
dc.subject.keywordPlus | Fat quantification | - |
dc.subject.keywordPlus | Field map estimations | - |
dc.subject.keywordPlus | Field map unwrapping | - |
dc.subject.keywordPlus | MR images | - |
dc.subject.keywordPlus | Region growing | - |
dc.subject.keywordPlus | Iterative methods | - |
dc.description.journalRegisteredClass | scopus | - |
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