Fig. 1

Study overview illustrating the use of original cardiac magnetic resonance (CMR) images for generation of synthetic short axis (SAX) and long axis (LAX) images using a progressive generative adversarial network (PG GAN). The resulting images were subjected to visual inspection by CMR experts and general cardiologists. In addition, deep learning segmentation networks (with U-Net design) were built based, both, on PG GAN and actual CMR frames. The accuracy of the resulting segmentation networks was finally compared on a separate data set not used for training of either network