Figure 2.

Flow of patient selection for VNE development and testing using clinical data sets. Clinical data sets used were from the University of Oxford Centre for Clinical Magnetic Resonance Research (OCMR) and the OxAMI study (Oxford Acute Myocardial Infarction). The training data set underwent strict late gadolinium enhancement (LGE) quality control to train the neural network to produce good-quality virtual native enhancement (VNE) images. The test data set went through initial rejection followed by multiobserver quality control. Rejected test data are available in Figures S1 and S4. *The generative adversarial network (GAN) translating postcontrast cine is specified in Supplemental Material 3. GBCA indicates gadolinium-based contrast agent; and LGE, late gadolinium enhancement.