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
Code for paper "Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy"
Code for the MIDL 2026 paper - Tagged-Informed Prior for Motion Quantification in Cine CMR Using Implicit Neural Representations
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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