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dc.contributor.authorLoizou, Christos P.en
dc.contributor.authorPattichis, Constantinos S.en
dc.contributor.authorSeimenis, Ioannisen
dc.contributor.authorEracleous, Eleni A.en
dc.contributor.authorSchizas, Christos N.en
dc.contributor.authorPantzaris, Marios C.en
dc.creatorLoizou, Christos P.en
dc.creatorPattichis, Constantinos S.en
dc.creatorSeimenis, Ioannisen
dc.creatorEracleous, Eleni A.en
dc.creatorSchizas, Christos N.en
dc.creatorPantzaris, Marios C.en
dc.date.accessioned2019-11-13T10:41:06Z
dc.date.available2019-11-13T10:41:06Z
dc.date.issued2008
dc.identifier.isbn978-1-4244-2255-5
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/54449
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 and abnormal tissue and in assessing disease progression. Shape and texture analysis was carried out in normal and diseased lesions in transverse sections of T2-weighted magnetic resonance (MR) images acquired from 10 symptomatic untreated subjects with clinically isolated syndrome (CIS) scanned twice, with an interval of 6-12 months. All detected brain lesions were manually segmented by an experienced neurologist and confirmed by a neuro-radiologist, whilst different shape and texture features were extracted from the segmented lesions. The results showed that there was no significance difference between shape features of 0 and 6-12 months. For some texture features there was significance difference between normal tissue and MS lesions at 0 and 6-12 months and between MS lesions at 0 and 6-12 months (i.e contrast, difference variance, difference entropy, and other). Further research with more subjects is required for computing shape and texture features that may provide information for differentiating between normal tissue and MS lesions as well as for longitudinal monitoring of these lesions. In addition the proposed methodology can be used for the assessment of subjects at risk of developing future neurological events. The extracted shape and features can also offer additional information of undiagnosed lesions. ©2008 IEEE.en
dc.source5th Int. Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd Int. Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008en
dc.source5th International Conference on Information Technology and Applications in Biomedicine, ITAB 2008 in conjunction with 2nd International Symposium and Summer School on Biomedical and Health Engineering, IS3BHE 2008en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-51849160892&doi=10.1109%2fITAB.2008.4570645&partnerID=40&md5=fdf288fdbd80043f98caa98734a08877
dc.subjectTechnologyen
dc.subjectRisk assessmenten
dc.subjectInformation technologyen
dc.subjectMultiple sclerosisen
dc.subjectHealthen
dc.subjectMagnetic resonance imagingen
dc.subjectSummer schoolsen
dc.subjectResonanceen
dc.subjectMagnetic resonanceen
dc.subjectInternational symposiumen
dc.subjectMagnetic fieldsen
dc.subjectImaging techniquesen
dc.subjectInternational conferencesen
dc.subjectHealth risksen
dc.subjectAtomsen
dc.subjectTexturesen
dc.subjectTexture featuresen
dc.subjectTechnology transferen
dc.subjectWhite matter lesionsen
dc.subjectBrain lesionsen
dc.subjectQuantitative analysisen
dc.subjectDisease progressionsen
dc.subjectLongitudinal monitoringen
dc.subjectMagnetic resonance (MR)en
dc.subjectMS lesionsen
dc.subjectNormal tissuesen
dc.subjectShape featuresen
dc.subjectTexture-analysisen
dc.subjectTransverse sectionsen
dc.titleQuantitative analysis of brain white matter lesions in multiple sclerosis subjects: Preliminary findingsen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.identifier.doi10.1109/ITAB.2008.4570645
dc.description.startingpage58
dc.description.endingpage61
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: Chinese Acad. Sci. Shenzhen Academician Consultation Centeren
dc.description.notesChinese University of Hong Kongen
dc.description.notesChinese Academy of Sciencesen
dc.description.notesInstitute of Biomedical and Health Engineeringen
dc.description.notesShenzhen Institute of Advanced Technologyen
dc.description.notesKey Laboratory for Biomedical Informatics and Health Engineeringen
dc.description.notesConference code: 73498en
dc.description.notesCited By :7</p>en
dc.contributor.orcidSchizas, Christos N. [0000-0001-6548-4980]
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.orcid0000-0001-6548-4980
dc.gnosis.orcid0000-0003-1271-8151
dc.gnosis.orcid0000-0003-1247-8573
dc.gnosis.orcid0000-0003-2937-384X


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