Simulator-generated training datasets as an alternative to using patient data for machine learning: An example in myocardial segmentation with MRI

•Development of advanced supervised ML techniques in MRI encounter limitations today•Main limitations involve lack of large and representative training datasets•Artificial MR-images can be used as training datasets in the MR field•A low-cost solution by means of MR simulations on computer models of human anatomy