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dc.contributor.authorLoizou, Christos P.en
dc.contributor.authorPattichis, Constantinos S.en
dc.contributor.authorSeimenis, Ioannisen
dc.contributor.authorPantzaris, Marios C.en
dc.creatorLoizou, Christos P.en
dc.creatorPattichis, Constantinos S.en
dc.creatorSeimenis, Ioannisen
dc.creatorPantzaris, Marios C.en
dc.date.accessioned2019-11-13T10:41:06Z
dc.date.available2019-11-13T10:41:06Z
dc.date.issued2009
dc.identifier.isbn978-1-4244-5379-5
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54450
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. ©2009 IEEE.en
dc.sourceFinal Program and Abstract Book - 9th International Conference on Information Technology and Applications in Biomedicine, ITAB 2009en
dc.source9th International Conference on Information Technology and Applications in Biomedicine, ITAB 2009en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77949595545&doi=10.1109%2fITAB.2009.5394340&partnerID=40&md5=8320f766f8c1a64d4641f4107b977a8d
dc.subjectInformation technologyen
dc.subjectMultiple sclerosisen
dc.subjectMagnetic resonance imagingen
dc.subjectMRIen
dc.subjectMagnetic resonanceen
dc.subjectTexturesen
dc.subjectTexture featuresen
dc.subjectTexture analysisen
dc.subjectWhite matteren
dc.subjectWhite matter lesionsen
dc.subjectNormal tissueen
dc.subjectTransverse sectionen
dc.subjectBrain lesionsen
dc.subjectQuantitative analysisen
dc.subjectShape featuresen
dc.subjectAbnormal tissuesen
dc.subjectMagnetic resonance imagesen
dc.titleQuantitative analysis of brain white matter lesions in multiple sclerosis subjectsen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/ITAB.2009.5394340
dc.author.faculty002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.departmentΤμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtypeConference Objecten
dc.description.notes<p>Sponsors: IBM Italia S.p.A.en
dc.description.notesDatamed SA, Healthcare Integratoren
dc.description.notesLinkSCEEM: Link. Sci. Comput. Eur. East. Mediterr.en
dc.description.notesAGIOS THERISSOS M.R.1. Medical Diagnostic Centeren
dc.description.notesUniversity of Cyprusen
dc.description.notesConference code: 79527en
dc.description.notesCited By :10</p>en
dc.contributor.orcidPattichis, Constantinos S. [0000-0003-1271-8151]
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.orcid0000-0003-1247-8573
dc.gnosis.orcid0000-0003-2937-384X


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