0 242

Cited 0 times in

Coloring of DT-MRI fiber Traces using Laplacian Eigenmaps

DC FieldValueLanguage
dc.contributor.author박해정-
dc.date.accessioned2016-05-16T11:01:25Z-
dc.date.available2016-05-16T11:01:25Z-
dc.date.issued2003-
dc.identifier.issn0302-9743-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/143617-
dc.description.abstractWe 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.statementOfResponsibilityopen-
dc.format.extent518~529-
dc.relation.isPartOfLecture Notes in Computer Science-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.subject.MESHSimilarity Measure-
dc.subject.MESHDiffusion Tensor-
dc.subject.MESHSeed Point-
dc.subject.MESHPost Processing Method-
dc.subject.MESHDiffusion Tensor Magnetic Resonance Image-
dc.titleColoring of DT-MRI fiber Traces using Laplacian Eigenmaps-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Nuclear Medicine (핵의학)-
dc.contributor.googleauthorAnders Brun-
dc.contributor.googleauthorHae Jeong Park-
dc.contributor.googleauthorHans Knutsson-
dc.contributor.googleauthorCarl-Fredrik Westin-
dc.identifier.doi10.1007/978-3-540-45210-2_47-
dc.admin.authorfalse-
dc.admin.mappingfalse-
dc.contributor.localIdA01730-
dc.relation.journalcodeJ02160-
dc.identifier.pmid10.1007/978-3-540-45210-2_47-
dc.identifier.urlhttp://link.springer.com/chapter/10.1007/978-3-540-45210-2_47-
dc.subject.keywordSimilarity Measure-
dc.subject.keywordDiffusion Tensor-
dc.subject.keywordSeed Point-
dc.subject.keywordPost Processing Method-
dc.subject.keywordDiffusion Tensor Magnetic Resonance Image-
dc.contributor.alternativeNamePark, Hae Jeong-
dc.contributor.affiliatedAuthorPark, Hae Jeong-
dc.rights.accessRightsnot free-
dc.citation.volume2809-
dc.citation.startPage518-
dc.citation.endPage529-
dc.identifier.bibliographicCitationLecture Notes in Computer Science, Vol.2809 : 518-529, 2003-
dc.identifier.rimsid38306-
dc.type.rimsART-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers

qrcode

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