250 citations · 272 across the 4 of their papers we have counts for
4 papers
Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix
Julian Krebs, Hervé Delingette, Nicholas Ayache +1
We propose to learn a probabilistic motion model from a sequence of images for spatio-temporal registration. Our model encodes motion in a low-dimensional probabilistic space - the…
Probabilistic Motion Modeling from Medical Image Sequences: Application to Cardiac Cine-MRI
Julian Krebs, Tommaso Mansi, Nicholas Ayache +1
We propose to learn a probabilistic motion model from a sequence of images. Besides spatio-temporal registration, our method offers to predict motion from a limited number of frame…
Learning a Probabilistic Model for Diffeomorphic Registration
Julian Krebs, Hervé Delingette, Boris Mailhé +2
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for registration and the analysis of deformations. The latent variable model maps…
Unsupervised Probabilistic Deformation Modeling for Robust Diffeomorphic Registration
Julian Krebs, Tommaso Mansi, Boris Mailhé +2
We propose a deformable registration algorithm based on unsupervised learning of a low-dimensional probabilistic parameterization of deformations. We model registration in a probab…