Early Prediction of Alzheimer's Disease with Non-local Patch-Based Longitudinal Descriptors

Gerard Sanroma 1, 2 Víctor Andrea 2 Oualid Benkarim 2 José Manjón 3 Pierrick Coupé 4, 5 Oscar Camara 1 Gemma Piella 1 Miguel González Ballester 2
1 Universitat Pompeu Fabra [Barcelona]
2 DITIC, universitat Pompeu Fabra
3 Universidad Politécnica de Valencia
4 PICTURA
LaBRI - Laboratoire Bordelais de Recherche en Informatique
5 LaBRI - Laboratoire Bordelais de Recherche en Informatique
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.
Keywords : early AD prediction non-local patch-based label fusion longitudinal analysis
Type de document :
Communication dans un congrès
International Workshop on Patch-based Techniques in Medical Imaging, Sep 2017, Québec, Canada. International Workshop on Patch-based Techniques in Medical Imaging, 〈10.1007/978-3-319-67434-6_9〉
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger
https://hal.archives-ouvertes.fr/hal-01626255
Contributeur : Pierrick Coupé <>
Soumis le : lundi 30 octobre 2017 - 15:20:33
Dernière modification le : vendredi 13 avril 2018 - 19:56:04
Document(s) archivé(s) le : mercredi 31 janvier 2018 - 12:54:16

Fichier

patchlong.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

UNIV-BORDEAUX | LABRI

Citation

Gerard Sanroma, Víctor Andrea, Oualid Benkarim, José Manjón, Pierrick Coupé, et al.. Early Prediction of Alzheimer's Disease with Non-local Patch-Based Longitudinal Descriptors. International Workshop on Patch-based Techniques in Medical Imaging, Sep 2017, Québec, Canada. International Workshop on Patch-based Techniques in Medical Imaging, 〈10.1007/978-3-319-67434-6_9〉. 〈hal-01626255〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

146

Téléchargements de fichiers

54

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD