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Conference Paper: A fast deformable region model for brain tumor boundary extraction

TitleA fast deformable region model for brain tumor boundary extraction
Authors
KeywordsMedical sciences
Computer applications
Issue Date2002
PublisherIEEE.
Citation
The 24th Joint Annual International Conference of the Engineering in Medicine and Biology Society Annual Fall Meeting of the Biomedical Engineering Society, Houston, Texas, USA, 23-26 October 2002, v. 2, p. 1055-1056 How to Cite?
AbstractWe present a modified deformable region model for extraction of a brain tumor boundary in 2D MR images. The deformable region model tolerates a rough initial plan when compared with the active contour model. However, it is time consuming to compute and compare the gray level distribution of the object and all its boundary points. Using a point sampling technique, the number of boundary point processed is greatly reduced. Performance of our modified deformable region model is evaluated on a MR image. The modified model is fast while similar results are obtained.
Persistent Identifierhttp://hdl.handle.net/10722/46377
ISSN

 

DC FieldValueLanguage
dc.contributor.authorLaw, AKWen_HK
dc.contributor.authorLam, FKen_HK
dc.contributor.authorChan, FHYen_HK
dc.date.accessioned2007-10-30T06:48:34Z-
dc.date.available2007-10-30T06:48:34Z-
dc.date.issued2002en_HK
dc.identifier.citationThe 24th Joint Annual International Conference of the Engineering in Medicine and Biology Society Annual Fall Meeting of the Biomedical Engineering Society, Houston, Texas, USA, 23-26 October 2002, v. 2, p. 1055-1056en_HK
dc.identifier.issn1094-687Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/46377-
dc.description.abstractWe present a modified deformable region model for extraction of a brain tumor boundary in 2D MR images. The deformable region model tolerates a rough initial plan when compared with the active contour model. However, it is time consuming to compute and compare the gray level distribution of the object and all its boundary points. Using a point sampling technique, the number of boundary point processed is greatly reduced. Performance of our modified deformable region model is evaluated on a MR image. The modified model is fast while similar results are obtained.en_HK
dc.format.extent254795 bytes-
dc.format.extent13817 bytes-
dc.format.extent8841 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2002 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectMedical sciencesen_HK
dc.subjectComputer applicationsen_HK
dc.titleA fast deformable region model for brain tumor boundary extractionen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1094-687X&volume=2&spage=1055&epage=1056&date=2002&atitle=A+fast+deformable+region+model+for+brain+tumor+boundary+extractionen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/IEMBS.2002.1106273en_HK
dc.identifier.hkuros81930-

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