This repository contains the official implementation of "Data-Agnostic Augmentations for Unknown Variations - Out-of-Distribution Generalisation in MRI Segmentation", under review at MIDL 2025.
Our work explores novel data augmentation techniques designed to improve model generalization in medical imaging, especially in scenarios with unseen domain shifts and rare cases.
Pretrained models and the testing data can be found at Zenodo.
