# uniGradICON: A Foundation Model for Medical Image Registration

arXiv: https://arxiv.org/abs/2403.05780 · HTML: https://mlsanity.com/paper/2403.05780/

## Key facts

- Cited by 58 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 35 references that are in the map.
- First posted on arXiv 9 Mar 2024.

## Builds on (most cited first, 15 of 15)

- [VoxelMorph: A Learning Framework for Deformable Medical Image Registration](https://mlsanity.com/paper/1809.05231/) (2018)
- [A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration](https://mlsanity.com/paper/1809.06130/) (2018)
- [Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks](https://mlsanity.com/paper/2006.16148/) (2020)
- [Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning](https://mlsanity.com/paper/2112.04489/) (2021)
- [Quicksilver: Fast Predictive Image Registration - a Deep Learning Approach](https://mlsanity.com/paper/1703.10908/) (2017)
- [Fast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks](https://mlsanity.com/paper/2003.09514/) (2020)
- [HyperMorph: Amortized Hyperparameter Learning for Image Registration](https://mlsanity.com/paper/2101.01035/) (2021)
- [End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network](https://mlsanity.com/paper/1704.06065/) (2017)
- [Networks for Joint Affine and Non-parametric Image Registration](https://mlsanity.com/paper/1903.08811/) (2019)
- [textttGradICON: Approximate Diffeomorphisms via Gradient Inverse Consistency](https://mlsanity.com/paper/2206.05897/) (2022)
- [Metric Learning for Image Registration](https://mlsanity.com/paper/1904.09524/) (2019)
- [ICON: Learning Regular Maps Through Inverse Consistency](https://mlsanity.com/paper/2105.04459/) (2021)
- [mlVIRNET: Multilevel Variational Image Registration Network](https://mlsanity.com/paper/1909.10084/) (2019)
- [Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration](https://mlsanity.com/paper/2402.18933/) (2024)
- [SAME++: A Self-supervised Anatomical eMbeddings Enhanced medical image registration framework using stable sampling and regularized transformation](https://mlsanity.com/paper/2311.14986/) (2023)

## Built on by (most cited first, 30 of 58)

- [Learning General-Purpose Biomedical Volume Representations using Randomized Synthesis](https://mlsanity.com/paper/2411.02372/) (2024)
- [multiGradICON: A Foundation Model for Multimodal Medical Image Registration](https://mlsanity.com/paper/2408.00221/) (2024)
- [LesionLocator: Zero-Shot Universal Tumor Segmentation and Tracking in 3D Whole-Body Imaging](https://mlsanity.com/paper/2502.20985/) (2025)
- [Beyond the LUMIR challenge: The pathway to foundational registration models](https://mlsanity.com/paper/2505.24160/) (2025)
- [Improving Generalization of Medical Image Registration Foundation Model](https://mlsanity.com/paper/2505.06527/) (2025)
- [Guiding Registration with Emergent Similarity from Pre-Trained Diffusion Models](https://mlsanity.com/paper/2506.02419/) (2025)
- [Deep Implicit Optimization enables Robust Learnable Features for Deformable Image Registration](https://mlsanity.com/paper/2406.07361/) (2024)
- [EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image Registration](https://mlsanity.com/paper/2403.11026/) (2024)
- [TimeFlow: Temporal Conditioning for Longitudinal Brain MRI Registration and Aging Analysis](https://mlsanity.com/paper/2501.08667/) (2025)
- [Zero-shot Domain Generalization of Foundational Models for 3D Medical Image Segmentation: An Experimental Study](https://mlsanity.com/paper/2503.22862/) (2025)
- [Encoder-Only Image Registration](https://mlsanity.com/paper/2509.00451/) (2025)
- [SAMReg: SAM-enabled Image Registration with ROI-based Correspondence](https://mlsanity.com/paper/2410.14083/) (2024)
- [CABLD: Contrast-Agnostic Brain Landmark Detection with Consistency-Based Regularization](https://mlsanity.com/paper/2411.17845/) (2024)
- [Unsupervised learning of spatially varying regularization for diffeomorphic image registration](https://mlsanity.com/paper/2412.17982/) (2024)
- [UniReg: Conditional Unified Model for Medical Image Registration](https://mlsanity.com/paper/2503.12868/) (2025)
- [PolyPose: Deformable 2D/3D Registration via Polyrigid Transformations](https://mlsanity.com/paper/2505.19256/) (2025)
- [TotalRegistrator: Towards a Lightweight Foundation Model for CT Image Registration](https://mlsanity.com/paper/2508.04450/) (2025)
- [The LUMirage: An independent evaluation of zero-shot performance in the LUMIR challenge](https://mlsanity.com/paper/2512.15505/) (2025)
- [On The Robustness of Foundational 3D Medical Image Segmentation Models Against Imprecise Visual Prompts](https://mlsanity.com/paper/2601.16383/) (2026)
- [CARL: A Framework for Equivariant Image Registration](https://mlsanity.com/paper/2405.16738/) (2024)
- [General Vision Encoder Features as Guidance in Medical Image Registration](https://mlsanity.com/paper/2407.13311/) (2024)
- [Large Scale Unsupervised Brain MRI Image Registration Solution for Learn2Reg 2024](https://mlsanity.com/paper/2409.00917/) (2024)
- [Improving Instance Optimization in Deformable Image Registration with Gradient Projection](https://mlsanity.com/paper/2410.15767/) (2024)
- [Implicit Deformable Medical Image Registration with Learnable Kernels](https://mlsanity.com/paper/2506.02150/) (2025)
- [Uncertainty Estimation for Pretrained Medical Image Registration Models via Transformation Equivariance](https://mlsanity.com/paper/2509.23355/) (2025)
- [A Scalable Distributed Framework for Multimodal GigaVoxel Image Registration](https://mlsanity.com/paper/2509.25044/) (2025)
- [A Denoising Framework for Real-World Ultra-Low-Dose Lung CT Images Based on an Image Purification Strategy](https://mlsanity.com/paper/2510.07492/) (2025)
- [MedSapiens: Taking a Pose to Rethink Medical Imaging Landmark Detection](https://mlsanity.com/paper/2511.04255/) (2025)
- [Statistical Opportunities in Neuroimaging](https://mlsanity.com/paper/2602.12974/) (2026)
- [Prior-Guided Implicit Neural Representations for Single-Subject Diffusion MRI Super-Resolution](https://mlsanity.com/paper/2609.00981/) (2026)

## Abstract (arXiv)

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 the uniGradICON model are available at https://github.com/uncbiag/uniGradICON.