Measuring brain variability via sulcal lines registration: a diffeomorphic approach.

Abstract : In this paper we present a new way of measuring brain variability based on the registration of sulcal lines sets in the large deformation framework. Lines are modelled geometrically as currents, avoiding then matchings based on point correspondences. At the end we retrieve a globally consistent deformation of the underlying brain space that best matches the lines. Thanks to this framework the measured variability is defined everywhere whereas a previous method introduced by P. Fillard requires tensors extrapolation. Evaluating both methods on the same database, we show that our new approach enables to describe different details of the variability and to highlight the major trends of deformation in the database thanks to a Tangent-PCA analysis.
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Communication dans un congrès
Nicholas Ayache and Sébastien Ourselin and Anthony Maeder. International Conference on Medical Imaging and Computer Assisted Intervention, Oct 2007, Brisbane, Australia. Springer-Verlag, 4791 (Pt 1), pp.675-82, 2007, Lecture notes in computer science. 〈10.1007/978-3-540-75757-3_82〉
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https://hal.inria.fr/inria-00502704
Contributeur : Stanley Durrleman <>
Soumis le : lundi 30 septembre 2013 - 16:47:40
Dernière modification le : vendredi 12 janvier 2018 - 01:55:24

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Stanley Durrleman, Xavier Pennec, Alain Trouvé, Nicholas Ayache. Measuring brain variability via sulcal lines registration: a diffeomorphic approach.. Nicholas Ayache and Sébastien Ourselin and Anthony Maeder. International Conference on Medical Imaging and Computer Assisted Intervention, Oct 2007, Brisbane, Australia. Springer-Verlag, 4791 (Pt 1), pp.675-82, 2007, Lecture notes in computer science. 〈10.1007/978-3-540-75757-3_82〉. 〈inria-00502704〉

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