Keywords: Image acquisition: Machine learning, Cardiovascular: Cardiac
Artificial intelligence (AI) is making a significant impact on all aspects of cardiovascular magnetic resonance (CMR) imaging. In this talk, we will focus on discussing the recent development of DL in CMR imaging workflow, from the reconstruction of accelerated signals to automatic quantification of clinically useful information. Specifically, we will describe how DL methods can be used for reconstruction of accelerated dynamic cine CMR imaging. We will also show the utility of DL for CMR analysis, with a particular focus on CMR segmentation and motion tracking. Finally, we will briefly discuss about their current limitations, challenges, and future opportunities.