Symmetric Log-Domain Diffeomorphic Registration: A Demons-based Approach

Abstract : Modern morphometric studies use non-linear image registration to compare anatomies and perform group analysis. Recently, log-Euclidean approaches have contributed to promote the use of such computational anatomy tools by permitting simple computations of statistics on a rather large class of invertible spatial transformations. In this work, we propose a non-linear registration algorithm perfectly fit for log-Euclidean statistics on diffeomorphisms. Our algorithm works completely in the log-domain, i.e. it uses a stationary velocity field. This implies that we guarantee the invertibility of the deformation and have access to the true inverse transformation. This also means that our output can be directly used for log-Euclidean statistics without relying on the heavy computation of the log of the spatial transformation. As it is often desirable, our algorithm is symmetric with respect to the order of the input images. Furthermore, we use an alternate optimization approach related to Thirion's demons algorithm to provide a fast non-linear registration algorithm. First results show that our algorithm outperforms both the demons algorithm and the recently proposed diffeomorphic demons algorithm in terms of accuracy of the transformation while remaining computationally efficient.
Type de document :
Communication dans un congrès
Dimitris Metaxas and Leon Axel and Gabor Fichtinger and Gábor Székely. Medical Image Computing and Computer Assisted Intervention, Sep 2008, New York, United States. Springer, 5241, pp.754--761, 2008, Lecture Notes in Computer Science - LNCS. 〈10.1007/978-3-540-85988-8_90〉
Liste complète des métadonnées

Littérature citée [17 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00280602
Contributeur : Tom Vercauteren <>
Soumis le : lundi 19 mai 2008 - 12:59:59
Dernière modification le : jeudi 11 janvier 2018 - 16:21:49
Document(s) archivé(s) le : vendredi 28 mai 2010 - 18:04:08

Fichier

SymLogDemons-MICCAI08-Vercaute...
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Tom Vercauteren, Xavier Pennec, Aymeric Perchant, Nicholas Ayache. Symmetric Log-Domain Diffeomorphic Registration: A Demons-based Approach. Dimitris Metaxas and Leon Axel and Gabor Fichtinger and Gábor Székely. Medical Image Computing and Computer Assisted Intervention, Sep 2008, New York, United States. Springer, 5241, pp.754--761, 2008, Lecture Notes in Computer Science - LNCS. 〈10.1007/978-3-540-85988-8_90〉. 〈inria-00280602〉

Partager

Métriques

Consultations de la notice

379

Téléchargements de fichiers

367