Εμφάνιση απλής εγγραφής

dc.contributor.authorLoizou, Christos P.en
dc.contributor.authorPantzaris, Marios C.en
dc.contributor.authorPattichis, Marios S.en
dc.contributor.authorKyriacou, Efthyvoulos C.en
dc.contributor.authorPattichis, Constantinos S.en
dc.creatorLoizou, Christos P.en
dc.creatorPantzaris, Marios C.en
dc.creatorPattichis, Marios S.en
dc.creatorKyriacou, Efthyvoulos C.en
dc.creatorPattichis, Constantinos S.en
dc.date.accessioned2019-11-13T10:41:04Z
dc.date.available2019-11-13T10:41:04Z
dc.date.issued2009
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54431
dc.description.abstractThe intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). It was proposed but not thoroughly investigated that the composition and texture of the media layer (ML) can be used as an indicator for the risk of stroke. In this study, we investigate the application of texture analysis of the ML of the CCA and how texture is affected by age and gender. The study was performed on 100 longitudinal-section ultrasound images acquired from asymptomatic subjects at risk of atherosclerosis. The images were separated into three different age groups, namely below 50, 50-60, and above 60 years old. Furthermore, the images were separated according to gender. A total of 61 different texture features were extracted from the intima layer (IL), the ML, and the intima-media complex (IMC). The ML and the IMC were segmented manually by a neurovascular expert and also automatically by a snakes segmentation system. We have found that male patients tended to have larger media layer thickness (MLT) values as compared to the MLT of female patients of the same age. We have found significant differences among texture features extracted from the IL, ML and IMC from different age groups. Furthermore, for some texture features, we found that they follow trends that correlate with a patient's age. For example, the gray-scale median GSM of the ML falls linearly with increasing MLT and with increasing age. Our findings suggest that ultrasound image texture analysis of the media layer has potential as an assessment biomarker for the risk of stroke. © 2009 Elsevier Ltd. All rights reserved.en
dc.sourceComputerized Medical Imaging and Graphicsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-63149168898&doi=10.1016%2fj.compmedimag.2009.02.005&partnerID=40&md5=1f57cfd2f14e23635ce8f393ef3f30bc
dc.subjectRisk analysisen
dc.subjectageen
dc.subjectAge Factorsen
dc.subjectarticleen
dc.subjectgenderen
dc.subjecthumanen
dc.subjectHumansen
dc.subjectadulten
dc.subjectageden
dc.subjectcontrolled studyen
dc.subjectfemaleen
dc.subjectMiddle Ageden
dc.subjectpriority journalen
dc.subjectAgingen
dc.subjectmaleen
dc.subjectrisk assessmenten
dc.subjectcorrelation analysisen
dc.subjectReproducibility of Resultsen
dc.subjectcardiovascular risken
dc.subjectgroups by ageen
dc.subjectultrasounden
dc.subjectcomparative studyen
dc.subjectSex Factorsen
dc.subjectStatistics as Topicen
dc.subjectTunica Intimaen
dc.subjectSensitivity and Specificityen
dc.subjectStrokeen
dc.subjectEchocardiographyen
dc.subjectUltrasonic imagingen
dc.subjectSemiconducting intermetallicsen
dc.subjectUltrasonicsen
dc.subjectChemical vapor depositionen
dc.subjectAged, 80 and overen
dc.subjectarterial wall thicknessen
dc.subjectatherosclerosisen
dc.subjectcommon carotid arteryen
dc.subjectTexturesen
dc.subjectCarotid Artery, Commonen
dc.subjectCarotid arteryen
dc.subjectTexture analysisen
dc.subjectImage Interpretation, Computer-Assisteden
dc.subjectAcoustic wavesen
dc.subjectUltrasound imageen
dc.subjectartery intimaen
dc.subjectartery mediaen
dc.subjectInitma-media layeren
dc.subjectIntima layeren
dc.subjectMedia layeren
dc.titleUltrasound image texture analysis of the intima and media layers of the common carotid artery and its correlation with age and genderen
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.compmedimag.2009.02.005
dc.description.volume33
dc.description.issue4
dc.description.startingpage317
dc.description.endingpage324
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 :25</p>en
dc.source.abbreviationComput.Med.Imaging Graph.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.contributor.orcidLoizou, Christos P. [0000-0003-1247-8573]
dc.contributor.orcidPantzaris, Marios C. [0000-0003-2937-384X]
dc.gnosis.orcid0000-0003-1271-8151
dc.gnosis.orcid0000-0002-1574-1827
dc.gnosis.orcid0000-0002-4589-519X
dc.gnosis.orcid0000-0003-1247-8573
dc.gnosis.orcid0000-0003-2937-384X


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