Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/192
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dc.contributorDepartment of Computing-
dc.creatorPang, B-
dc.creatorZhang, DD-
dc.creatorWang, K-
dc.date.accessioned2014-12-11T08:23:02Z-
dc.date.available2014-12-11T08:23:02Z-
dc.identifier.issn0278-0062 (print)-
dc.identifier.issn1558-254X (online)-
dc.identifier.urihttp://hdl.handle.net/10397/192-
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.rights© 2005 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_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectChinese medicineen_US
dc.subjectDeformable templatesen_US
dc.subjectMedical biometricsen_US
dc.subjectSnakesen_US
dc.subjectTongue image segmentationen_US
dc.titleThe bi-elliptical deformable contour and its application to automated tongue segmentation in Chinese medicineen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage946-
dc.identifier.epage956-
dc.identifier.volume24-
dc.identifier.issue8-
dc.identifier.doi10.1109/TMI.2005.850552-
dcterms.abstractAutomated tongue image segmentation, in Chinese medicine, is difficult due to two special factors: 1) there are many pathological details on the surface of the tongue, which have a large influence on edge extraction; 2) the shapes of the tongue bodies captured from various persons (with different diseases) are quite different, so they are impossible to describe properly using a predefined deformable template. To address these problems, in this paper, we propose an original technique that is based on a combination of a bi-elliptical deformable template (BEDT) and an active contour model, namely the bi-elliptical deformable contour (BEDC). The BEDT captures gross shape features by using the steepest decent method on its energy function in the parameter space. The BEDC is derived from the BEDT by substituting template forces for classical internal forces, and can deform to fit local details. Our algorithm features fully automatic interpretation of tongue images and a consistent combination of global and local controls via the template force. We apply the BEDC to a large set of clinical tongue images and present experimental results.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationIEEE transactions on medical imaging, Aug. 2005, v. 24, no. 8, p. 946-956-
dcterms.isPartOfIEEE transactions on medical imaging-
dcterms.issued2005-08-
dc.identifier.isiWOS:000230851800002-
dc.identifier.scopus2-s2.0-23844535467-
dc.identifier.rosgroupidr26672-
dc.description.ros2005-2006 > Academic research: refereed > Publication in refereed journal-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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