Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23611
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dc.contributor.authorLoizou, Christos P.-
dc.contributor.authorMurray, Víctor-
dc.contributor.authorPattichis, Marios S.-
dc.contributor.authorPantziaris, Marios-
dc.contributor.authorSeimenis, Ioannis-
dc.contributor.authorPattichis, Constantinos S.-
dc.date.accessioned2021-11-10T12:08:02Z-
dc.date.available2021-11-10T12:08:02Z-
dc.date.issued2010-05-
dc.identifier.citation12th Mediterranean Conference on Medical and Biological Engineering and Computing, 2010, 27-30 May, Chalkidiki, Greeceen_US
dc.identifier.isbn978-3-642-13039-7-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/23611-
dc.description.abstractIn this study we investigate the use of multiscale Amplitude Modulation-Frequency Modulation (AM-FM) methods for analyzing brain white matter lesions that are associated with multiple sclerosis MRI lesions imaged at 0 and 6-12 months. We use the instantaneous amplitude (IA) and the instantaneous frequency (IF) to assess disease progression. The IA and the IF were calculated in transverse sections of T2- weighted magnetic resonance (MR) images acquired from 38 symptomatic untreated subjects between the first and the second examination scan. The findings suggest that the high-, medium-, and low- frequency scale instantaneous amplitude and frequency can be used to differentiate between normal tissue and lesions at 0 and 6-12 months. Moreover, support vector machine (SVM) models gave satisfactory results for differentiating lesions at 0 months using the medium scale IA and IF components for expanded disability status scale (EDSS) <=2 and EDSS >2. Further work is needed with more subjects in validating the proposed AM-FM analysis. © 2010 International Federation for Medical and Biological Engineering.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofMediterranean Conference on Medical and Biological Engineering and Computingen_US
dc.rights© Springeren_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMultiple sclerosisen_US
dc.subjectAM-FM analysisen_US
dc.subjectBrain white matteren_US
dc.subjectDisease progressionen_US
dc.titleAM-FM texture image analysis in multiple sclerosis brain white matter lesionsen_US
dc.typeConference Papersen_US
dc.collaborationIntercollegeen_US
dc.collaborationUniversity of New Mexicoen_US
dc.collaborationCyprus Institute of Neurology and Geneticsen_US
dc.collaborationAyios Therissos Medical Diagnostic Centeren_US
dc.collaborationUniversity of Cyprusen_US
dc.subject.categoryMedical Engineeringen_US
dc.countryCyprusen_US
dc.countryUnited Statesen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1007/978-3-642-13039-7_112en_US
dc.identifier.scopus2-s2.0-77957582021-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/77957582021-
cut.common.academicyear2009-2010en_US
dc.identifier.spage446en_US
dc.identifier.epage449en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.fulltextNo Fulltext-
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-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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