bibtext: @InProceedings{ Tia_uniGradICON_MICCAI2024,
                   author = { Tian, Lin and Greer, Hastings and Kwitt, Roland and Vialard, François-Xavier and San José Estépar, Raúl and Bouix, Sylvain and Rushmore, Richard and Niethammer, Marc },
                   title = { { uniGradICON: A Foundation Model for Medical Image Registration } },
                   booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024},
                   year = {2024},
                   publisher = {Springer Nature Switzerland},
                   volume = { LNCS 15002 },
                   month = {October},
                   pages = { pending },
                }
abstract: Conventional medical image registration approaches directly optimize over the parameters of a transformation model. These approaches have been highly successful and are used generically for registrations of different anatomical regions. Recent deep registration networks are incredibly fast and accurate but are only trained for specific tasks. Hence, they are no longer generic registration approaches. We therefore propose uniGradICON, a first step toward a foundation model for registration providing 1) great performance 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. UniGradICON unifies the speed and accuracy benefits of learning-based registration algorithms with the generic applicability of conventional non-deep-learning approaches. We extensively trained and evaluated uniGradICON on twelve different public datasets. Our code and weight are available at https://github.com/uncbiag/uniGradICON.
title: uniGradICON: A Foundation Model for Medical Image Registration
authors: Tian, Lin Greer, Hastings Kwitt, Roland Vialard, François-Xavier San José Estépar, Raúl Bouix, Sylvain Rushmore, Richard Niethammer, Marc