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Coloring of DT-MRI fiber Traces using Laplacian Eigenmaps
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박해정 | - |
dc.date.accessioned | 2016-05-16T11:01:25Z | - |
dc.date.available | 2016-05-16T11:01:25Z | - |
dc.date.issued | 2003 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/143617 | - |
dc.description.abstract | We propose a novel post processing method for visualization of fiber traces from DT-MRI data. Using a recently proposed non-linear dimensionality reduction technique, Laplacian eigenmaps [3], we create a mapping from a set of fiber traces to a low dimensional Euclidean space. Laplacian eigenmaps constructs this mapping so that similar traces are mapped to similar points, given a custom made pairwise similarity measure for fiber traces. We demonstrate that when the low-dimensional space is the RGB color space, this can be used to visualize fiber traces in a way which enhances the perception of fiber bundles and connectivity in the human brain. | - |
dc.description.statementOfResponsibility | open | - |
dc.format.extent | 518~529 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/2.0/kr/ | - |
dc.subject.MESH | Similarity Measure | - |
dc.subject.MESH | Diffusion Tensor | - |
dc.subject.MESH | Seed Point | - |
dc.subject.MESH | Post Processing Method | - |
dc.subject.MESH | Diffusion Tensor Magnetic Resonance Image | - |
dc.title | Coloring of DT-MRI fiber Traces using Laplacian Eigenmaps | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Nuclear Medicine (핵의학) | - |
dc.contributor.googleauthor | Anders Brun | - |
dc.contributor.googleauthor | Hae Jeong Park | - |
dc.contributor.googleauthor | Hans Knutsson | - |
dc.contributor.googleauthor | Carl-Fredrik Westin | - |
dc.identifier.doi | 10.1007/978-3-540-45210-2_47 | - |
dc.admin.author | false | - |
dc.admin.mapping | false | - |
dc.contributor.localId | A01730 | - |
dc.relation.journalcode | J02160 | - |
dc.identifier.pmid | 10.1007/978-3-540-45210-2_47 | - |
dc.identifier.url | http://link.springer.com/chapter/10.1007/978-3-540-45210-2_47 | - |
dc.subject.keyword | Similarity Measure | - |
dc.subject.keyword | Diffusion Tensor | - |
dc.subject.keyword | Seed Point | - |
dc.subject.keyword | Post Processing Method | - |
dc.subject.keyword | Diffusion Tensor Magnetic Resonance Image | - |
dc.contributor.alternativeName | Park, Hae Jeong | - |
dc.contributor.affiliatedAuthor | Park, Hae Jeong | - |
dc.rights.accessRights | not free | - |
dc.citation.volume | 2809 | - |
dc.citation.startPage | 518 | - |
dc.citation.endPage | 529 | - |
dc.identifier.bibliographicCitation | Lecture Notes in Computer Science, Vol.2809 : 518-529, 2003 | - |
dc.identifier.rimsid | 38306 | - |
dc.type.rims | ART | - |
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