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.
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Journal ArticleDOI
Computation of a probabilistic statistical shape model in a maximum-a-posteriori framework.
TL;DR: A method to represent a mean shape and a variability model for a training data set based on probabilistic correspondence computed between the observations based on maximum-a-posteriori framework leads to very efficient and closed-form solutions for (almost) all parameters.
Book ChapterDOI
A Statistical Model of Right Ventricle in Tetralogy of Fallot for Prediction of Remodelling and Therapy Planning
Tommaso Mansi,Stanley Durrleman,Boris C. Bernhardt,Maxime Sermesant,Hervé Delingette,Ingmar Voigt,Philipp Lurz,Andrew M. Taylor,Julie Blanc,Younes Boudjemline,Xavier Pennec,Nicholas Ayache +11 more
TL;DR: In this paper, a forward model based on currents and LDDMM algorithm was proposed to estimate an unbiased template of 18 patients and the deformations towards each individual shape, and the statistically significant deformation modes were found clinically relevant.
Book ChapterDOI
Tracking Medical 3D Data with a Deformable Parametric Model
TL;DR: A new approach to surface tracking applied to 3D medical data with a deformable model based on a parametric model composed of a superquadric fit followed by a Free-Form Deformation that gives a compact representation of a set of points in a 3D image.
Journal ArticleDOI
Parsimonious Approximation of Streamline Trajectories in White Matter Fiber Bundles
Pietro Gori,Olivier Colliot,Linda Marrakchi-Kacem,Yulia Worbe,Fabrizio De Vico Fallani,Mario Chavez,Cyril Poupon,Andreas Hartmann,Nicholas Ayache,Stanley Durrleman +9 more
TL;DR: An iterative algorithm which approximates independently and simultaneously all the fascicles of the bundle in a fast and accurate way is proposed which drastically reduces the computational burden of the processes where the geometry of the streamlines is considered.
Journal ArticleDOI
An augmented reality system to guide radio-frequency tumour ablation: Research Articles
TL;DR: An augmented reality system for hepatic therapy guidance that superimposes in real-time 3D reconstructions and a virtual model of the needle on external views of a patient and is highly accurate and enables the surgeon to reach a target in less than 1 minute on average.