1 code implementation • 9 Mar 2024 • Lin Tian, Hastings Greer, Roland Kwitt, Francois-Xavier Vialard, Raul San Jose Estepar, Sylvain Bouix, Richard Rushmore, Marc Niethammer
We therefore propose uniGradICON, a first step toward a foundation model for registration providing 1) great performance \emph{across} multiple datasets which is not feasible for current learning-based registration methods, 2) zero-shot capabilities for new registration tasks suitable for different acquisitions, anatomical regions, and modalities compared to the training dataset, and 3) a strong initialization for finetuning on out-of-distribution registration tasks.
1 code implementation • 28 Apr 2023 • Hastings Greer, Lin Tian, Francois-Xavier Vialard, Roland Kwitt, Sylvain Bouix, Raul San Jose Estepar, Richard Rushmore, Marc Niethammer
Inverse consistency is a desirable property for image registration.
2 code implementations • ICCV 2021 • Hastings Greer, Roland Kwitt, Francois-Xavier Vialard, Marc Niethammer
We explore if it is possible to obtain spatial regularity using an inverse consistency loss only and elucidate what explains map regularity in such a context.
no code implementations • 13 Jan 2021 • Adrien Vacher, Boris Muzellec, Alessandro Rudi, Francis Bach, Francois-Xavier Vialard
It is well-known that plug-in statistical estimation of optimal transport suffers from the curse of dimensionality.
Statistics Theory Optimization and Control Statistics Theory 62G05
1 code implementation • CVPR 2019 • Marc Niethammer, Roland Kwitt, Francois-Xavier Vialard
Our approach is a radical departure from existing deep learning approaches to image registration by embedding a deep learning model in an optimization-based registration algorithm to parameterize and data-adapt the registration model itself.
Ranked #1 on Diffeomorphic Medical Image Registration on CUMC12
Deformable Medical Image Registration Diffeomorphic Medical Image Registration +2