Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23674
DC FieldValueLanguage
dc.contributor.authorLoizou, Christos P.-
dc.date.accessioned2021-11-23T09:02:03Z-
dc.date.available2021-11-23T09:02:03Z-
dc.date.issued2005-09-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/23674-
dc.description.abstractStroke is one of the most important causes of death in the world and the leading cause of serious, long-term disability. There is an urgent need for better techniques to diagnose patients at risk of stroke based on the measurements of the intima media thickness (IMT) and the segmentation of the atherosclerotic carotid plaque. The objective of this work was to carry out a comparative evaluation of despeckle filtering on ultrasound images of the carotid artery, and develop a new segmentation system, for detecting the IMT of the common carotid artery and the borders of the athrerosclerotic carotid plaque in longitudinal ultrasound images of the carotid artery. To the best of our knowledge no similar system has been developed for segmenting the atherosclerotic carotid plaque, although a number of techniques have been proposed for IMT segmentation. A total of 11 despeckle filtering methods were evaluated based on texture analysis, image quality evaluation metrics, and visual evaluation made by two experts, on 440 ultrasound images of the carotid artery bifurcation. Furthermore, the proposed IMT and plaque segmentation techniques were evaluated on 100 and 80 longitudinal ultrasound images of the carotid bifurcation respectively based on receiver operating chatracteristic (ROC) analysis. The despeckle filtering results showed that a despeckle filter based on local statistics (lsmv) improved the class separation between asymptomatic and symptomatic classes, gave only a marginal improvement in the percentage of correct classifications success rate, and improved the visual assessment carried out by the experts. It was also found that the lsmv despeckle filter can be used for despeckling asymptomatic images where the expert is interested mainly in the plaque composition and texture analysis, whereas a geometric despeckle filter (gf4d) can be used for despeckling of symptomatic images where the expert is interested in identifying the degree of stenosis and the plaque borders. The IMT snakes segmentation results showed that no significant difference was found between the manual and the snakes segmentation measurements. Better segmentation results were obtained for the normalized despeckled images. The plaque segmentation results showed that, the Lai&Chin snakes segmentation method gives results comparable to the manual delineation procedure. The IMT and plaque snakes segmentation method may be therefore used to complement and assist the final expert’s evaluation. The proposed despeckling and segmentation methods will be further evaluated on a larger number of ultrasound images and on multiple experts’ evaluation. Furthermore, it is expected that both methods will be incorporated into an integrated system enabling the texture analysis of the segmented plaque, providing an automated system for the early diagnosis and the assessment of the risk of stroke.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectStrokeen_US
dc.subjectIntima media thicknessen_US
dc.subjectAtherosclerotic carotid plaqueen_US
dc.subjectComparative evaluationen_US
dc.subjectDespeckle filteringen_US
dc.subjectUltrasound imagesen_US
dc.titleUltrasound image analysis of the carotid arteryen_US
dc.typeBooken_US
dc.collaborationKingston Universityen_US
dc.subject.categoryMedical Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
cut.common.academicyear2005-2006en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_2f33-
item.openairetypebook-
item.languageiso639-1en-
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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