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Conference Paper: A semi-automatic clustering-based level set method for segmentation of endocardium from MSCT images

TitleA semi-automatic clustering-based level set method for segmentation of endocardium from MSCT images
Authors
Issue Date2007
PublisherIEEE.
Citation
The 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Lyon, France, 23-26 August 2007. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, p. 6023-6026 How to Cite?
AbstractMulti-slice Computed Tomography (MSCT) is an important medical imaging tool that provides dynamic three-dimensional (3D) volume data of the heart for diagnosis of various cardiac diseases. Due to the huge amount of data in MSCT, manual identification, segmentation and tracking of various parts of the heart are very labor intensive and inefficient. In this paper, we introduce a semi-automatic method for robustly segmenting the endocardium surface from cardiac MSCT images. A level set approach is adopted to define a flexible and powerful interface for capturing the complex anatomical structure of the heart. A novel speed function based on clustering the image intensities of the region of interest and the background is proposed for use with the level set method. The method introduced in this paper has the advantages of simple initialization and being capable of segmenting the blood pool with non-homogeneous intensities. Experiments on real data using the proposed speed function have been carried out with 2D, 3D and 4D implementations of the level sets respectively, and comparisons in terms of computational speed and segmentation results are presented. © 2007 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/137145
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorSu, Qen_HK
dc.contributor.authorWong, KYKen_HK
dc.contributor.authorFung, GSKen_HK
dc.date.accessioned2011-08-24T03:58:33Z-
dc.date.available2011-08-24T03:58:33Z-
dc.date.issued2007en_HK
dc.identifier.citationThe 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Lyon, France, 23-26 August 2007. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, p. 6023-6026en_HK
dc.identifier.issn0589-1019en_HK
dc.identifier.urihttp://hdl.handle.net/10722/137145-
dc.description.abstractMulti-slice Computed Tomography (MSCT) is an important medical imaging tool that provides dynamic three-dimensional (3D) volume data of the heart for diagnosis of various cardiac diseases. Due to the huge amount of data in MSCT, manual identification, segmentation and tracking of various parts of the heart are very labor intensive and inefficient. In this paper, we introduce a semi-automatic method for robustly segmenting the endocardium surface from cardiac MSCT images. A level set approach is adopted to define a flexible and powerful interface for capturing the complex anatomical structure of the heart. A novel speed function based on clustering the image intensities of the region of interest and the background is proposed for use with the level set method. The method introduced in this paper has the advantages of simple initialization and being capable of segmenting the blood pool with non-homogeneous intensities. Experiments on real data using the proposed speed function have been carried out with 2D, 3D and 4D implementations of the level sets respectively, and comparisons in terms of computational speed and segmentation results are presented. © 2007 IEEE.en_HK
dc.languageeng-
dc.publisherIEEE.-
dc.relation.ispartofProceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Societyen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsIEEE Engineering in Medicine and Biology Society Conference Proceedings. Copyright © IEEE.-
dc.rights©2007 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.-
dc.subject.meshAlgorithms-
dc.subject.meshArtificial Intelligence-
dc.subject.meshCluster Analysis-
dc.subject.meshEndocardium - radiography-
dc.subject.meshImaging, Three-Dimensional - instrumentation - methods-
dc.titleA semi-automatic clustering-based level set method for segmentation of endocardium from MSCT imagesen_HK
dc.typeConference_Paperen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1557-170X&volume=2007&spage=6023&epage=6026&date=2007&atitle=A+semi-automatic+clustering-based+level+set+method+for+segmentation+of+endocardium+from+MSCT+images-
dc.identifier.emailWong, KYK:kykwong@cs.hku.hken_HK
dc.identifier.authorityWong, KYK=rp01393en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/IEMBS.2007.4353721en_HK
dc.identifier.pmid18003387-
dc.identifier.scopuseid_2-s2.0-57649232174en_HK
dc.identifier.hkuros143886-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-57649232174&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume2007-
dc.identifier.spage6023en_HK
dc.identifier.epage6026en_HK
dc.publisher.placeUnited Statesen_HK
dc.description.otherThe 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), Lyon, France, 23-26 August 2007. In Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, p. 6023-6026-
dc.identifier.scopusauthoridSu, Q=55224418800en_HK
dc.identifier.scopusauthoridWong, KYK=24402187900en_HK
dc.identifier.scopusauthoridFung, GSK=7004213392en_HK

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