The MYOSAIQ Challenge: Myocardial Segmentation with Automated Infarct Quantification
Late gadolinium enhancement (LGE) cardiac magnetic resonance (MR) imaging is the modality of choice to assess myocardial infarction (MI) lesions. Nowadays MI volume quantification is not performed routinely in clinical practice. Numerous deep learning (DL) methods have been developed to automate the segmentation of the myocardium and infarct regions. However, most studies rely on relatively small datasets which typically undergo pre-processing steps to standardize images and focus on a specific phase of myocardial infarction following reperfusion therapy. These limitations have impeded the development of models that are generalizable across diverse conditions and thus suitable for routine...
| Authors | Olivier Bernard, William A. Romero R., Cyprien Bouton et al. |
|---|---|
| Primary category | eess.IV |
| Published | 29 August 2026 |
| Last updated at source | 29 August 2026 |
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