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dc.contributor.authorKyriacou, Efthyvoulos C.en
dc.contributor.authorPattichis, Constantinos S.en
dc.contributor.authorPattichis, Marios S.en
dc.contributor.authorMavrommatis, A.en
dc.contributor.authorPanagiotou, S.en
dc.contributor.authorChristodoulou, Christodoulos I.en
dc.contributor.authorKakkos, Stavros K.en
dc.contributor.authorNicolaïdes, Andrew N.en
dc.contributor.editorMaglogiannis, I.en
dc.contributor.editorKarpouzis, K.en
dc.contributor.editorBramer M.en
dc.creatorKyriacou, Efthyvoulos C.en
dc.creatorPattichis, Constantinos S.en
dc.creatorPattichis, Marios S.en
dc.creatorMavrommatis, A.en
dc.creatorPanagiotou, S.en
dc.creatorChristodoulou, Christodoulos I.en
dc.creatorKakkos, Stavros K.en
dc.creatorNicolaïdes, Andrew N.en
dc.date.accessioned2019-11-13T10:40:52Z
dc.date.available2019-11-13T10:40:52Z
dc.date.issued2006
dc.identifier.issn1571-5736
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54336
dc.description.abstractThe aim of this study was to investigate the usefulness of gray scale morphological analysis in the assessment of atherosclerotic carotid plagues. Ultrasound images were recorded from 137 asymptomatic and 137 symptomatic plaques (Stroke, Transient Ischaemic Attack -TLA, Amaurosis Fugax-AF). The morphological pattern spectra of gray scale images were computed and two different classifiers named the Probabilistic Neural Network (PNN) and the Support Vector Machine (SVM) were evaluated for classifying these spectra into two classes: asymptomatic or symptomatic. The highest percentage of correct classifications score was 66,8% and was achieved using the SVM classifier. This score is slightly lower than texture analysis carried out on the same data set. © 2006 International Federation for Information Processing.en
dc.sourceIFIP International Federation for Information Processingen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-33749128064&doi=10.1007%2f0-387-34224-9_87&partnerID=40&md5=048025f0300b8311a92ecd30fc9f5859
dc.titleClassification of atherosclerotic carotid plaques using gray level morphological analysis on ultrasound imagesen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1007/0-387-34224-9_87
dc.description.volume204
dc.description.startingpage737
dc.description.endingpage744
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeArticleen
dc.description.notes<p>Cited By :3</p>en
dc.source.abbreviationIFIP Int. Fed. Inf. Process.en
dc.contributor.orcidPattichis, Constantinos S. [0000-0003-1271-8151]
dc.contributor.orcidPattichis, Marios S. [0000-0002-1574-1827]
dc.contributor.orcidKyriacou, Efthyvoulos C. [0000-0002-4589-519X]
dc.gnosis.orcid0000-0003-1271-8151
dc.gnosis.orcid0000-0002-1574-1827
dc.gnosis.orcid0000-0002-4589-519X


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