Early prediction of Alzheimer's disease with non-local patch-based longitudinal descriptors

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• dc.contributor.author Sanromà, Gerard
• dc.contributor.author Andrea, Víctor
• dc.contributor.author Benkarim, Oualid M.
• dc.contributor.author Manjón, José V.
• dc.contributor.author Coupé, Pierrick
• dc.contributor.author Camara, Oscar
• dc.contributor.author Piella Fenoy, Gemma
• dc.contributor.author González Ballester, Miguel Ángel, 1973-
• dc.date.accessioned 2019-03-05T16:08:45Z
• dc.date.available 2019-03-05T16:08:45Z
• dc.date.issued 2017
• dc.description Comunicació presentada a: the 3rd International Workshop on Patch-based Techniques in Medical Imaging, amb conjunció amb MICCAI, celebrat a Québec, Canadà, el 14 de setembre de 2017.ca
• dc.description.abstract Alzheimer’s disease (AD) is characterized by a progressive decline in the cognitive functions accompanied by an atrophic process which can already be observed in the early stages using magnetic resonance images (MRI). Individualized prediction of future progression to AD, when patients are still in the mild cognitive impairment (MCI) stage, has potential impact for preventive treatment. Atrophy patterns extracted from longitudinal MRI sequences provide valuable information to identify MCI patients at higher risk of developing AD in the future. We present a novel descriptor that uses the similarity between local image patches to encode local displacements due to atrophy between a pair of longitudinal MRI scans. Using a conventional logistic regression classifier, our descriptor achieves 76% accuracy in predicting which MCI patients will progress to AD up to 3 years before conversion.en
• dc.description.sponsorship The first author is co-financed by the Marie Curie FP7-PEOPLE-2012-COFUND 462 Action. Grant agreement no: 600387.en
• dc.format.mimetype application/pdf
• dc.identifier.citation Sanroma G, Andrea V, Benkarim OM, Manjón JV, Coupé P, Camara O, Piella G, González Ballester MA. Early prediction of Alzheimer's disease with non-local patch-based longitudinal descriptors. In: Wu G, Munsell BC, Zhan Y, Bai W, Sanroma G, Coupé P, editors. Patch-Based Techniques in Medical Imaging: 3rd International Workshop on Patch-based Techniques in Medical Imaging; 2017 Sep 14; Québec, Canada. [Cham]: Springer; 2017. p. 74-81. (LNCS; no. 10530). DOI: 10.1007/978-3-319-67434-6_9
• dc.identifier.doi http://dx.doi.org/10.1007/978-3-319-67434-6_9
• dc.identifier.isbn 9783319674339
• dc.identifier.issn 0302-9743
• dc.identifier.uri http://hdl.handle.net/10230/36744
• dc.language.iso eng
• dc.publisher Springer
• dc.relation.ispartof Wu G, Munsell BC, Zhan Y, Bai W, Sanroma G, Coupé P, editors. Patch-Based Techniques in Medical Imaging: 3rd International Workshop on Patch-based Techniques in Medical Imaging; 2017 Sep 14; Québec, Canada. [Cham]: Springer; 2017. p. 74-81. (LNCS; no. 10530).
• dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/600387
• dc.rights © Springer The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-67434-6_9
• dc.rights.accessRights info:eu-repo/semantics/openAccess
• dc.subject.keyword Early AD predictionen
• dc.subject.keyword Non-local patch-based label fusionen
• dc.subject.keyword Longitudinal analysisen
• dc.title Early prediction of Alzheimer's disease with non-local patch-based longitudinal descriptors
• dc.type info:eu-repo/semantics/conferenceObject
• dc.type.version info:eu-repo/semantics/acceptedVersion