Sparse-Based Morphometry: Principle and Application to Alzheimer's Disease

Pierrick Coupé 1 Charles Deledalle 2 Charles Dossal 2 Michèle Allard 3
1 LaBRI - Laboratoire Bordelais de Recherche en Informatique
2 IMB - Institut de Mathématiques de Bordeaux
3 INCIA - Institut de Neurosciences cognitives et intégratives d'Aquitaine
Abstract : The detection of brain alterations is crucial for understanding pathophysiological or neurodegenerative processes. The Voxel-Based Morphometry (VBM) is one of the most popular methods to achieve this task. Based on the comparison of local averages of tissue densities, VBM has been used in a large number of studies. Despite its numerous advantages , VBM is based on a highly reduced representation of the local brain anatomy since complex anatomical patterns are reduced to local averages of tissue probabilities. In this paper, we propose a new framework called Sparse-Based Morphometry (SBM) to better represent local brain anatomies. The presented patch-based approach uses dictionary learning to detect anatomical pattern modifications based on their shape and geometry. In our validation, the impact of the patch and group sizes is evaluated. Moreover, the sensitivity of SBM along Alzheimer's Disease (AD) progression is compared to VBM. Our results indicate that SBM is more sensitive than VBM on small groups and to detect early anatomical modifications caused by AD.
Keywords : voxel-based morphometry Alzheimer's Disease dictionary learning abnormality detection patch-based processing
Type de document :
Communication dans un congrès
Patch-Based Techniques in Medical Imaging, Oct 2016, Athènes, Greece. Lecture Notes in Computer Science, Patch-Based Techniques in Medical Imaging. 〈10.1007/978-3-319-47118-1_6〉
Liste complète des métadonnées

Littérature citée [13 références]  Voir  Masquer  Télécharger
https://hal.archives-ouvertes.fr/hal-01398763
Contributeur : Pierrick Coupé <>
Soumis le : jeudi 17 novembre 2016 - 16:46:54
Dernière modification le : jeudi 11 janvier 2018 - 06:25:29
Document(s) archivé(s) le : jeudi 16 mars 2017 - 16:34:32

Fichier

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

Identifiants

Collections

UNIV-BORDEAUX | LABRI | IMB

Citation

Pierrick Coupé, Charles Deledalle, Charles Dossal, Michèle Allard. Sparse-Based Morphometry: Principle and Application to Alzheimer's Disease. Patch-Based Techniques in Medical Imaging, Oct 2016, Athènes, Greece. Lecture Notes in Computer Science, Patch-Based Techniques in Medical Imaging. 〈10.1007/978-3-319-47118-1_6〉. 〈hal-01398763〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

110

Téléchargements de fichiers

60

Contact

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