Detailed Information

Cited 0 time in webofscience Cited 3 time in scopus
Metadata Downloads

Automatic human brain vessel segmentation from 3D 7 Tesla MRA images using fast marching with anisotropic directional prior

Full metadata record
DC Field Value Language
dc.contributor.authorLiao, W.-
dc.contributor.authorRohr, K.-
dc.contributor.authorKang, C.-K.-
dc.contributor.authorCho, Z.-H.-
dc.contributor.authorWörz, S.-
dc.date.available2020-02-29T09:44:36Z-
dc.date.created2020-02-11-
dc.date.issued2012-
dc.identifier.issn1945-7928-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/17465-
dc.description.abstractAccurate 3D models of the human brain vessels can greatly help to diagnose serious diseases. Such models can be constructed by segmentation of 3D MRA images, especially the recently introduced high resolution 7T MRA. We propose a new two-step approach for fully automatic segmentation of 7T MRA images of the human cerebrovascular system. First, a 3D model-based approach is applied to segment thick vessels and most parts of thin vessels. Then, the missing vessel parts, which are caused by low contrast and high noise, are completed using a novel fast marching approach with anisotropic directional prior. An evaluation of our approach and a comparison with two previous approaches have been conducted using high resolution 3D 7T MRA images. © 2012 IEEE.-
dc.language영어-
dc.language.isoen-
dc.relation.isPartOfProceedings - International Symposium on Biomedical Imaging-
dc.subject3D models-
dc.subject3D segmentation-
dc.subject7T MRA-
dc.subjectAutomatic segmentations-
dc.subjectFast-marching-
dc.subjectHigh noise-
dc.subjectHigh resolution-
dc.subjectHuman brain-
dc.subjectLow contrast-
dc.subjectModel based approach-
dc.subjectMRA images-
dc.subjectThin vessels-
dc.subjectTwo-step approach-
dc.subjectVasculature-
dc.subjectAnisotropy-
dc.subjectBrain-
dc.subjectImage segmentation-
dc.subjectMedical imaging-
dc.subjectThree dimensional-
dc.titleAutomatic human brain vessel segmentation from 3D 7 Tesla MRA images using fast marching with anisotropic directional prior-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.doi10.1109/ISBI.2012.6235761-
dc.identifier.bibliographicCitationProceedings - International Symposium on Biomedical Imaging, pp.1140 - 1143-
dc.identifier.scopusid2-s2.0-84864847749-
dc.citation.endPage1143-
dc.citation.startPage1140-
dc.citation.titleProceedings - International Symposium on Biomedical Imaging-
dc.contributor.affiliatedAuthorKang, C.-K.-
dc.contributor.affiliatedAuthorCho, Z.-H.-
dc.type.docTypeConference Paper-
dc.subject.keywordAuthor7T MRA-
dc.subject.keywordAuthoranisotropic fast marching-
dc.subject.keywordAuthorAutomatic 3D segmentation-
dc.subject.keywordAuthorCerebral vasculature-
dc.subject.keywordPlus3D models-
dc.subject.keywordPlus3D segmentation-
dc.subject.keywordPlus7T MRA-
dc.subject.keywordPlusAutomatic segmentations-
dc.subject.keywordPlusFast-marching-
dc.subject.keywordPlusHigh noise-
dc.subject.keywordPlusHigh resolution-
dc.subject.keywordPlusHuman brain-
dc.subject.keywordPlusLow contrast-
dc.subject.keywordPlusModel based approach-
dc.subject.keywordPlusMRA images-
dc.subject.keywordPlusThin vessels-
dc.subject.keywordPlusTwo-step approach-
dc.subject.keywordPlusVasculature-
dc.subject.keywordPlusAnisotropy-
dc.subject.keywordPlusBrain-
dc.subject.keywordPlusImage segmentation-
dc.subject.keywordPlusMedical imaging-
dc.subject.keywordPlusThree dimensional-
dc.description.journalRegisteredClassscopus-
Files in This Item
There are no files associated with this item.
Appears in
Collections
보건과학대학 > 방사선학과 > 1. Journal Articles

qrcode

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

Related Researcher

Researcher Kang, Chang Ki photo

Kang, Chang Ki
Health Science (Dept.of Radiology)
Read more

Altmetrics

Total Views & Downloads

BROWSE