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dc.contributor.authorLeandrou, Stephanos
dc.contributor.authorPetroudi, Styliani
dc.contributor.authorKyriacou, Panicos A.
dc.contributor.authorReyes-Aldasoro, Constantino Carlos
dc.contributor.authorPattichis, C. S.
dc.creatorLeandrou, Stephanos
dc.date.accessioned2018-12-05T14:13:22Z
dc.date.available2018-12-05T14:13:22Z
dc.date.issued2016-01-01
dc.identifierSCOPUS_ID:84968563048
dc.identifier.isbn9783319327013
dc.identifier.issn16800737
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84968563048&origin=inward
dc.identifier.urihttps://repo.euc.ac.cy/handle/123456789/1140
dc.description.abstractMedical image analysis and visualization, can contribute in quantitative and qualitative analysis of Magnetic Resonance Imaging (MRI) towards an earlier diagnosis of Alzheimer’s disease (AD). Moreover, the early detection of Mild Cognitive Impairment (MCI) has recently attracted a lot of attention. The main objective of this paper is to present a survey of recent key papers focused on the classification of MCI and AD and the prediction of conversion from MCI to AD using volume, shape and texture analysis. The most frequent anatomical features used in the assessment of AD, is the hippocampus, the cortex and the local concentration of grey matter. Shape analysis can identify the signs of early hippocampal atrophy, whereas volume analysis evaluates the structure as a whole. Shape analysis seems to be a more accurate technique both in classification of patients and in prognostic prediction. Compared to volume, shape and voxel based morphometry (VBM) techniques, texture analysis can be used to identify the microstructural changes before the larger-scale morphological characteristics which are detected by the other aforementioned techniques. We concluded that quantitative MRI measurements can be used as an in vivo surrogate for the classification of patients and furthermore, for the tracking the Alzheimer’s disease progression.
dc.relation.ispartofIFMBE Proceedings
dc.titleAn overview of quantitative magnetic resonance imaging analysis studies in the assessment of alzheimer’s disease
elsevier.identifier.doi10.1007/978-3-319-32703-7_56
elsevier.identifier.eid2-s2.0-84968563048
elsevier.identifier.scopusidSCOPUS_ID:84968563048
elsevier.volume57
elsevier.coverdate2016-01-01
elsevier.coverdisplaydate2016
elsevier.openaccess0
elsevier.openaccessflagfalse
elsevier.aggregationtypeConference Proceeding


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