Artificial intelligence (AI) will give radiologists more time to interpret images and cut the time they spend on paperwork.

The highest hurdle to widespread clinical usage of AI algorithms will be their seamless integration into clinical workflows, as often they increase the time spent on protocols, which was actually less in the old pen-and-paper days.

Prostate cancer is the second leading cause of cancer death in men, affecting about one in eight. Here are a few ways AI advances are improving accuracy and efficiency in prostate imaging.

Cardiac magnetic resonance imaging (CMR) has become increasingly important in clinical management of patients with a wide array of congenital and acquired cardiovascular conditions. CMR provides structural, anatomical, and physiologic data in conveniently reviewable image sets which are highly reproducible, enabling easy comparison of previous and/or subsequent examinations. These capabilities only scratch the surface of what CRM is able to do in clinical practice, however.

The field of radiomics has recently undergone marked growth. The goal in radiomics is to discover features in medical images using algorithmic evaluation of pixel/voxel data that can give valuable and potentially actionable clinical insights. This involves more precise and repeatable characterization of the features physicians use and finding features not apparent on human visual inspection. If radiomics provide post contrast imaging information without the need for contrast this may shorten scan times and also obviate the need for intravenous (IV) access and gadolinium administration.