Power Euclidean metrics for covariance matrices with application to diffusion tensor imaging

Abstract : Various metrics for comparing diffusion tensors have been recently proposed in the literature. We consider a broad family of metrics which is indexed by a single power parameter. A likelihood-based procedure is developed for choosing the most appropriate metric from the family for a given dataset at hand. The approach is analogous to using the Box-Cox transformation that is frequently investigated in regression analysis. The methodology is illustrated with a simulation study and an application to a real dataset of diffusion tensor images of canine hearts.
Liste complète des métadonnées

https://hal.inria.fr/hal-00813769
Contributeur : Project-Team Asclepios <>
Soumis le : jeudi 2 mai 2013 - 17:03:29
Dernière modification le : jeudi 11 janvier 2018 - 16:40:44

Lien texte intégral

Identifiants

  • HAL Id : hal-00813769, version 1
  • ARXIV : 1009.3045

Collections

Citation

I. L. Dryden, Xavier Pennec, Jean-Marc Peyrat. Power Euclidean metrics for covariance matrices with application to diffusion tensor imaging. ArXiv e-prints. 2010. 〈hal-00813769〉

Partager

Métriques

Consultations de la notice

309