Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30642
DC FieldValueLanguage
dc.contributor.authorConstantinou, Kyriacos P.-
dc.contributor.authorConstantinou, Ioannis P.-
dc.contributor.authorPattichis, Marios S.-
dc.contributor.authorKyriacou, Efthyvoulos C.-
dc.contributor.authorPattichis, Constantinos S.-
dc.date.accessioned2023-10-12T09:46:12Z-
dc.date.available2023-10-12T09:46:12Z-
dc.date.issued2023-06-11-
dc.identifier.citation24th International Conference on Digital Signal Processing, DSP 2023, Rhodes, Greece, 11 - 13 June 2023en_US
dc.identifier.isbn9798350339598-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/30642-
dc.description.abstractThe objective of this work was the investigation of multiscale Amplitude Modulation - Frequency Modulation (AM-FM) analysis based on Difference of Gaussians (DoG) filterbanks representations in order to predict the risk of stroke by analysing carotid plaques ultrasound images of individuals with asymptomatic carotid stenosis. We computed the instantaneous amplitude, instantaneous phase and the magnitude of instantaneous frequency to extract histogram features on each plaque region. The Support Vectors Machine classifier was implemented to classify asymptomatic versus symptomatic plaques. A dataset of 100 carotid plaque images (50 asymptomatic and 50 symptomatic) were tested, and showed that the AM-FM features based on DoG filterbanks and simple histograms performed better than the traditional AM-FM features. Best results were obtained when an eight scale filterbank with a combination of scales was used reaching the accuracy of 75%.en_US
dc.language.isoenen_US
dc.rights© IEEEen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAmplitude Modulation - Frequency Modulation (AM-FM)en_US
dc.subjectCarotid plaqueen_US
dc.subjectClassificationen_US
dc.subjectDifference of Gaussiansen_US
dc.subjectUltrasound imagingen_US
dc.titleCarotid plaque stroke risk assessment using multiscale AM-FM analysis based on DoG filterbanksen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationIstognosis Ltden_US
dc.collaborationUniversity of New Mexicoen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryElectrical Engineering - Electronic Engineering - Information Engineeringen_US
dc.countryCyprusen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.relation.conferenceInternational Conference on Digital Signal Processingen_US
dc.identifier.doi10.1109/DSP58604.2023.10167874en_US
dc.identifier.scopus2-s2.0-85165469177-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85165469177-
cut.common.academicyear2022-2023en_US
item.fulltextNo Fulltext-
item.languageiso639-1en-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.cerifentitytypePublications-
item.openairetypeconferenceObject-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4589-519X-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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