Deep Learning for Automated Segmentation of Left Ventricle Myocardium and Myocardial Scar From 3-D MR Images

150 150 MaLMIC - Machine Learning in Medical Imaging Consortium

Open Forum on Machine Learning in Cardiac Imaging


Fatemeh Zabihollahy


Deep learning has demonstrated promise for various cardiac imaging applications. However, the performance is usually degraded when the models are trained with small and under-annotated training datasets and tested on previously unseen domains, limiting the potential for broad clinical use. In this talk, Fumin presented his recent work on combining deep learning and machine learning models for cardiac MRI segmentation, where smaller datasets and fewer annotations are required for algorithm training. He also provided examples of integrating the segmentation tools for myocardial infarct heterogeneity quantification in contrast enhancement MRI in the context of MRI-guided cardiac arrhythmia treatment.


  • MR


  • Cardiac


  • Heart Disease
  • Stroke and Cardiovascular