Synopsis

Real-time cardiac MRI allows for the application of cardiac MRI to broader patient populations. Real-time CMR involves rapid data acquisition while free-breathing, and is typically independent of ECG-gating. Undersampled k-space acquisitions combined with advanced reconstruction methods are essential for real-time CMR. Compressed sensing (CS) is a popular approach that involves data sampling patterns that generate incoherent artifacts and uses iterative L1 norm constrained reconstructions. However, CS reconstructions are time-consuming. Deep-learning reconstructions offer real-time reconstructions from undersampled data as well as rapid automatic post-processing. The talk will give an overview of technical aspects for some of the real-time applications.