Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/23646
DC FieldValueLanguage
dc.contributor.authorLoizou, Christos P.-
dc.contributor.authorPattichis, Constantinos S.-
dc.contributor.authorSeimenis, Ioannis-
dc.contributor.authorPantziaris, Marios-
dc.date.accessioned2021-11-16T06:01:15Z-
dc.date.available2021-11-16T06:01:15Z-
dc.date.issued2010-01-22-
dc.identifier.citation9th International Conference on Information Technology and Applications in Biomedicine, 2009, 4-7 November, Larnaka, Cyprusen_US
dc.identifier.isbn9781424453795-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/23646-
dc.description.abstractIn this study the value of magnetic resonance image (MRI) shape and texture analysis was assessed in multiple sclerosis (MS) subjects, both in differentiating between normal or normal appearing and abnormal tissue and in assessing disease onset. Shape and texture analysis was carried out in normal brain white matter and lesions detected in transverse sections of T2-weighted magnetic resonance (MR) images acquired from 22 symptomatic untreated subjects. All detected brain lesions were manually segmented by an experienced MS neurologist and confirmed by a radiologist. The results showed that there was no significant difference for most of the shape features and for all of the texture features between MS lesions at 0 and 6-12 months. For some texture features there was significant difference between normal or normal appearing tissue and MS lesions at 0 and 6-12 months. Further research with more subjects is required for computing shape and texture features that may provide information for better and earlier differentiation between normal tissue and MS lesions.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.rights© IEEEen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMRIen_US
dc.subjectMultiple sclerosisen_US
dc.subjectShape featuresen_US
dc.subjectTexture analysisen_US
dc.titleQuantitative analysis of brain white matter lesions in multiple sclerosis subjectsen_US
dc.typeConference Papersen_US
dc.collaborationIntercollegeen_US
dc.collaborationUniversity of Cyprusen_US
dc.collaborationAyios Therissos Medical Diagnostic Centeren_US
dc.collaborationCyprus Institute of Neurology and Geneticsen_US
dc.subject.categoryMedical Engineeringen_US
dc.countryCyprusen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceIEEE International Conference on Information Technology and Applications in Biomedicineen_US
dc.identifier.doi10.1109/ITAB.2009.5394340en_US
dc.identifier.scopus2-s2.0-77949595545-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/77949595545-
cut.common.academicyear2009-2010en_US
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
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-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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