CineMA - A Foundation Model for Cine Cardiac Magnetic Resonance Images 🎥🫀
CineMA is a foundation model for Cine cardiac magnetic resonance (CMR) imaging based on Masked-Autoencoder. CineMA has been pre-trained on UK Biobank data and fine-tuned on multiple clinically relevant tasks such as ventricle and myocaridum segmentation, ejection fraction (EF) regression, cardiovascular disease (CVD) detection and classification, and mid-valve plane and apical landmark localization. The model has been evaluated on multiple datasets, including ACDC, M&Ms, M&Ms2, Kaggle, Rescan, and Landmark, etc.
➡️ Manuscript: https://arxiv.org/abs/2506.00679.
➡️ Code: mathpluscode/CineMA
Fine-tuned CineMA Models
The filenames of fine-tuned model weights follow the convention of
finetuned/<task>/<data>_<view>/<data>_<view>_<seed>.safetensors where number 0, 1, and 2 correspond to the different
training seeds.
Check the "Inference Example" column to see example inference scripts using these trained models.
Pre-trained CineMA Model
The pre-trained CineMA model backbone is available at pretrained/cinema.safetensors with configuration pretrained/config.yaml.
Following scripts demonstrated how to fine-tune this backbone using a preprocessed version of ACDC dataset:
- Ventricle and myocardium segmentation
- Cardiovascular disease classification
- Ejection fraction regression
Citation
Contact
For questions or collaborations, please contact Yunguan Fu (yunguan.fu.18@ucl.ac.uk).