Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23641
DC FieldValueLanguage
dc.contributor.authorLoizou, Christos P.-
dc.contributor.authorPattichis, Constantinos S.-
dc.contributor.authorPantziaris, Marios-
dc.contributor.authorNicolaides, Andrew N.-
dc.date.accessioned2021-11-15T11:13:53Z-
dc.date.available2021-11-15T11:13:53Z-
dc.date.issued2007-11-
dc.identifier.citationIEEE Transactions on Information Technology in Biomedicine, 2007, vol. 11, no. 6, pp. 661 - 667en_US
dc.identifier.issn15580032-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/23641-
dc.description.abstractIn this paper, we propose and evaluate an integrated system for the segmentation of atherosclerotic plaque in ultrasound imaging of the carotid artery based on normalization, speckle reduction filtering, and four different snakes segmentation methods. These methods are the Williams and Shah, Balloon, Lai and Chin, and the gradient vector flow (GVF) snake. The performance of the four different plaque snakes segmentation methods was tested on 80 longitudinal ultrasound images of the carotid artery using receiver operating characteristic (ROC) analysis and the manual delineations of an expert. All four methods were very satisfactory and similar in all measures evaluated, with no significant differences between them; however, the Lai and Chin snakes segmentation method gave slightly better results. Concluding, it is proposed that the integrated system investigated in this study could be used successfully for the automated segmentation of the carotid plaque.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofIEEE Transactions on Information Technology in Biomedicineen_US
dc.rights© IEEEen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAtherosclerosisen_US
dc.subjectCarotid plaqueen_US
dc.subjectSnakesen_US
dc.subjectUltrasound imagingen_US
dc.titleAn integrated system for the segmentation of atherosclerotic carotid plaqueen_US
dc.typeArticleen_US
dc.collaborationIntercollegeen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationCyprus Institute of Neurology and Geneticsen_US
dc.collaborationVascular Screening and Diagnostic Centeren_US
dc.subject.categoryMedical Engineeringen_US
dc.journalsSubscriptionen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1109/titb.2006.890019en_US
dc.identifier.pmid18046941-
dc.identifier.scopus2-s2.0-36349029691-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/36349029691-
dc.relation.issue6en_US
dc.relation.volume11en_US
cut.common.academicyear2007-2008en_US
dc.identifier.spage661en_US
dc.identifier.epage667en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.languageiso639-1en-
crisitem.journal.journalissn1089-7771-
crisitem.journal.publisherIEEE-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0003-1247-8573-
crisitem.author.parentorgFaculty of Engineering and Technology-
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