Herve Delingette

Université Côte d’Azur, Inria, Epione Team, Sophia Antipolis, France

Associated articles

TBME, Featured Articles
Non-Invasive Personalisation of a Cardiac Electrophysiology Model from Body Surface Potential Mapping
We use non-invasive data (body surface potential mapping, BSPM) to personalize the main parameters of a cardiac electrophysiological model for predicting the response to different pacing conditions. First, an efficient forward model is proposed, coupling the Mitchell-Schaeffer transmembrane potential model with... Read more
TMI, Featured Articles
Learning a Probabilistic Model for Diffeomorphic Registration
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The latent variable model maps similar deformations close to each other in an encoding space. It enables... Read more