A Framework for Uncertainty and Validation of 3D Registration Methods based on Points and Frames

Xavier Pennec 1, * Jean-Philippe Thirion 1
* Auteur correspondant
1 EPIDAURE - Medical imaging and robotics
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : In this paper, we propose and analyze several methods to estimate a rigid transformation from a set of 3D matched points or matched frames, which are important features in geometric algorithms. We also develop tools to predict and verify the accuracy of these estimations. The theoretical contributions are: an intrinsic model of noise for transformations based on composition rather than addition; a unified formalism for the estimation of both the rigid transformation and its covariance matrix for points or frames correspondences, and a statistical validation method to verify the error estimation, which applies even when no "ground truth" is available. We analyze and demonstrate on synthetic data that our scheme is well behaved. The practical contribution of the paper is the validation of our transformation estimation method in the case of 3D medical images, which shows that an accuracy of the registration far below the size of a voxel can be achieved, and in the case of protein substructure matching, where frame features drastically improve both selectivity and complexity.
Liste complète des métadonnées

Littérature citée [49 références]  Voir  Masquer  Télécharger

Contributeur : Project-Team Asclepios <>
Soumis le : mercredi 17 août 2011 - 23:28:30
Dernière modification le : samedi 27 janvier 2018 - 01:30:42
Document(s) archivé(s) le : vendredi 25 novembre 2011 - 11:27:54


Fichiers produits par l'(les) auteur(s)




Xavier Pennec, Jean-Philippe Thirion. A Framework for Uncertainty and Validation of 3D Registration Methods based on Points and Frames. International Journal of Computer Vision, Springer Verlag, 1997, 25 (3), pp.203-229. 〈10.1023/A:1007976002485〉. 〈inria-00615070〉



Consultations de la notice


Téléchargements de fichiers