Morphometry of anatomical shape complexes with dense deformations and sparse parameters

Abstract : We propose a generic method for the statistical analysis of collections of anatomical shape complexes, namely sets of surfaces that were previously segmented and labeled in a group of subjects. The method estimates an anatomical model, the template complex, that is representative of the population under study. Its shape reflects anatomical invariants within the dataset. In addition, the method automatically places control points near the most variable parts of the template complex. Vectors attached to these points are parameters of deformations of the ambient 3D space. These deformations warp the template to each subject's complex in a way that preserves the organization of the anatomical structures. Multivariate statistical analysis is applied to these deformation parameters to test for group differences (...)
Type de document :
Article dans une revue
NeuroImage, Elsevier, 2014, 〈10.1016/j.neuroimage.2014.06.043〉
Liste complète des métadonnées

Littérature citée [33 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01015771
Contributeur : Stanley Durrleman <>
Soumis le : vendredi 27 juin 2014 - 10:10:17
Dernière modification le : vendredi 25 mai 2018 - 12:02:06
Document(s) archivé(s) le : samedi 27 septembre 2014 - 10:51:26

Fichier

2013_Neuroimage_Durrleman_auth...
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Stanley Durrleman, Marcel Prastawa, Nicolas Charon, Julie R Korenberg, S. Joshi, et al.. Morphometry of anatomical shape complexes with dense deformations and sparse parameters. NeuroImage, Elsevier, 2014, 〈10.1016/j.neuroimage.2014.06.043〉. 〈hal-01015771〉

Partager

Métriques

Consultations de la notice

558

Téléchargements de fichiers

255