Deep Learning-Based Estimation of Myocardial Material Parameters from Cardiac MRI

This study establishes a computationally efficient and accurate deep learning framework for estimating myocardial material parameters, eliminating the need for time-consuming iterative FE optimization. While the model shows promising performance on healthy subjects, further validation and refinement are required to address its limitations in pathological conditions, thereby paving the way for personalized cardiac modeling and improved clinical decision-making.