N
Nicholas Ayache
Researcher at French Institute for Research in Computer Science and Automation
Publications - 639
Citations - 47063
Nicholas Ayache is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Segmentation & Image registration. The author has an hindex of 97, co-authored 624 publications receiving 43140 citations. Previous affiliations of Nicholas Ayache include University of Las Palmas de Gran Canaria & Mauna Kea Technologies.
Papers
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Journal Article
Machine Vision for Medicine of 21st Century.
TL;DR: A list of such problems including rigid and deformable registration of multimodal brain images, motion analysis from dynamic sequences of cardiac images, and soft-tissue modeling for liver surgery is presented.
Proceedings Article
Technical Appendix on Sparse Bayesian Regression
TL;DR: A sparse bayesian approach to regression can be seen as an extension of the Relevance Vector Machine of Tipping to a more general setting that can handle vector-valued regression and generic quadratic priors.
Patent
Dispositif de traitement d'informations d'images tridimensionnelles, avec extraction de lignes remarquables
TL;DR: In this paper, the authors define an image (MI) en correspondance of a maillage polyedrique predetermine d'une portion of l'espace, par une valeur numerique pour chaque sommet du maillages.
Book ChapterDOI
Velocity-Based Cardiac Contractility Personalization with Derivative-Free Optimization
Ken C. L. Wong,Maxime Sermesant,Jatin Relan,Kawal Rhode,Matthew Ginks,C. Aldo Rinaldi,Reza Razavi,Hervé Delingette,Nicholas Ayache +8 more
TL;DR: This work proposes a velocity-based objective function on identifying the maximum contraction, contraction rate, and relaxation rate simultaneously with intact model complexity, and shows that the framework can obtain personalized contractility consistent to the physiologies of the patients.
Journal ArticleDOI
Détermination d'un modèle biomécanique du cerveau par l'analyse d'images: application à la maladie de ParkinsonDetermination of a biomechanical model of the brain by magnetic resonance images: application to Parkinson's disease
TL;DR: A patient-specific biomechanical model of the brain able to recover its global deformation during this type of neurosurgical procedure could be used to update the pre-operative planning and to predict the mechanical effects of the intra-operative brain shift.