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Conference Paper: Semi-automatic tumor boundary detection in MR image sequences

TitleSemi-automatic tumor boundary detection in MR image sequences
Authors
Issue Date2001
PublisherIEEE.
Citation
International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2-4 May 2001, p. 28-31 How to Cite?
AbstractThe authors present a semi-automatic approach for the detection of tumor boundary in MR image sequences. An initial slice with an obvious tumor is selected from the image sequence. The tumor is roughly segmented using fuzzy c-means algorithm and its boundary can be further refined by region and contour deformation. For the rest of the slices, the initial plan applied for each slice is extracted from the resulting boundary of the previous slice. The tumor boundary is located using region and contour deformation. Performance of our approach is evaluated on the MR image sequence. Comparisons with manual tracing show the accuracy and effectiveness of our approach.
Persistent Identifierhttp://hdl.handle.net/10722/46219
ISBN

 

DC FieldValueLanguage
dc.contributor.authorLaw, AKWen_HK
dc.contributor.authorZhu, Hen_HK
dc.contributor.authorChan, BCBen_HK
dc.contributor.authorLu, PPen_HK
dc.contributor.authorLam, FKen_HK
dc.contributor.authorChan, FHYen_HK
dc.date.accessioned2007-10-30T06:45:03Z-
dc.date.available2007-10-30T06:45:03Z-
dc.date.issued2001en_HK
dc.identifier.citationInternational Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, 2-4 May 2001, p. 28-31en_HK
dc.identifier.isbn962-85766-2-3en_HK
dc.identifier.urihttp://hdl.handle.net/10722/46219-
dc.description.abstractThe authors present a semi-automatic approach for the detection of tumor boundary in MR image sequences. An initial slice with an obvious tumor is selected from the image sequence. The tumor is roughly segmented using fuzzy c-means algorithm and its boundary can be further refined by region and contour deformation. For the rest of the slices, the initial plan applied for each slice is extracted from the resulting boundary of the previous slice. The tumor boundary is located using region and contour deformation. Performance of our approach is evaluated on the MR image sequence. Comparisons with manual tracing show the accuracy and effectiveness of our approach.en_HK
dc.format.extent402079 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.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.rights©2001 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.titleSemi-automatic tumor boundary detection in MR image sequencesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=962-85766-2-3&volume=&spage=28&epage=31&date=2001&atitle=Semi-automatic+tumor+boundary+detection+in+MR+image+sequencesen_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/ISIMP.2001.925322en_HK
dc.identifier.hkuros58534-

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