Please find our public repositories here, which showcase our work on AI in healthcare.
Useful links:
- About us
- We host many of our algorithms on grand-challenge.org, where you can try them out. Contact us if you'd like to gain access.
Please find our public repositories here, which showcase our work on AI in healthcare.
Useful links:
Code for training and inference of a 3D CNN for whole-heart segmentation in CCTA
Example code for making an inference algorithm for the AIROGS challenge
Autoencoding of low-resolution MRI for Super-Resolution of anisotropic MRI
UBIX is a method to improve the generalizability of classification models, by introducing built-in robustness to dataset-specific (out-of-distribution) artifacts, without requiring any additional t…
Python 5
Code for the MIDL 2026 paper - Tagged-Informed Prior for Motion Quantification in Cine CMR Using Implicit Neural Representations
Code for paper "Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy"
Code for the SPIE Medical Imaging 2026 paper - Fighting MRI Anisotropy: Learning Multiple Cardiac Shapes From a Single Implicit Neural Representation.
Code accompanying the 2026 SPIE paper 'Dual-Phase Cross-Modal Contrastive Learning for CMR-Guided ECG Representations for Cardiovascular Disease Assessment'
PyTorch implementation of the Bounding Box Network (BoBNet) from the ConvNet-Based Localization of Anatomical Structures in 3D Medical Images paper.
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