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Feature selection for brain tumour classification using ratios of metabolites' peak areas from MRSI data

A. Heerschap, Zervakis Michalis, G.J. Postma, L.M.C. Buydens, M.E. Blazadonakis

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URIhttp://purl.tuc.gr/dl/dias/91F093D4-8436-49F7-B84F-2D059E032A59-
Languageen-
Extent6 pagesen
TitleFeature selection for brain tumour classification using ratios of metabolites' peak areas from MRSI data en
Creator A. Heerschapen
CreatorZervakis Michalisen
CreatorΖερβακης Μιχαληςel
CreatorG.J. Postmaen
CreatorL.M.C. Buydensen
CreatorM.E. Blazadonakis en
Content SummaryThe main goal of this study was threefold. Firstly, to investigate the significance of the brain metabolites' peak area Ratios derived from the MRSI spectra provided, by performing brain tumor binary classification and comparing the result with those obtained by using only the metabolites' Peak Amplitudes. Secondly to measure the influence of the four magnetic resonance image intensities (MRI) on the classification process and thirdly to estimate the minimum but also biologically significant set of featuresen
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-25-
Date of Publication2008-
SubjectBasic medical sciencesen
SubjectBasic sciences, Medicalen
SubjectBiomedical sciencesen
SubjectHealth sciencesen
SubjectPreclinical sciencesen
SubjectSciences, Medicalen
Subjectmedical sciencesen
Subjectbasic medical sciencesen
Subjectbasic sciences medicalen
Subjectbiomedical sciencesen
Subjecthealth sciencesen
Subjectpreclinical sciencesen
Subjectsciences medicalen
Bibliographic CitationM.G. Kounelakis, M.E.Zervakis, M.E. Blazadonakis, G.J. Postma, L.M.C. Buydens, A. Heerschap, X. Kotsiakis ,"Feature selection for brain tumour classification using ratios of metabolites' peak areas from MRSI data,"in 6th European Symposium on Biomedical Engineering ESBME,2008, pp.1-6.en

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