A Hough transform global approach to diffusion MRI tractography

Ehsan Aganj; Christophe Lenglet; Renaud Keriven; Guillermo Sapiro; Noam Harel; Paul Thompson

A Hough transform global approach to diffusion MRI tractography

Ehsan Aganj ^{1, 2} Christophe Lenglet ^{3, 4} Renaud Keriven ^{2, 1} Guillermo Sapiro ⁴ Noam Harel ³ Paul Thompson ⁵

1 LIGM - Laboratoire d'Informatique Gaspard-Monge

CSTB - Centre Scientifique et Technique du Bâtiment, LIGM - Laboratoire d'Informatique Gaspard-Monge, ENPC - École des Ponts ParisTech

3 CMRR - Center for Magnetic Resonance Research [Minneapolis]

4 ECE - Department of Electrical and Computer Engineering [Minneapolis]

5 LONI - Laboratory of Neuro Imaging [Los Angeles]

Abstract : Tractography in Diffusion-Weighted MRI provides a unique quantitative measurement of the brain's anatomical connectivity using information not available from other imaging techniques. Many tractography algorithms are based on local fiber orientation estimates, such as streamline methods, and are vulnerable to noise and partial volume effects; fiber crossing and kissing are also difficult to distinguish. This led to the development of probabilistic techniques [1] and global approaches relying on front propagation [2, 3] or simulation of the diffusion process [4]. In this work, we present a global approach based on the voting process provided by the Hough transform [5]. Our proposed tractography algorithm essentially tests all possible 3D curves in the volume, assigning a score to each of them, then selecting the curves with the highest scores, and returning them as the potential anatomical connections. We present experimental results on both artificial and real diffusion tensor images (DTI) and high-angular resolution diffusion images (HARDI).

Type de document :

Communication dans un congrès

Domaine :

Informatique [cs] / Vision par ordinateur et reconnaissance de formes [cs.CV]

Liste complète des métadonnées

https://hal-enpc.archives-ouvertes.fr/hal-00834965
Contributeur : Pascal Monasse <>
Soumis le : lundi 17 juin 2013 - 16:47:59
Dernière modification le : jeudi 7 février 2019 - 16:51:23
Document(s) archivé(s) le : mercredi 18 septembre 2013 - 04:17:50

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