Review of the Current State of Artificial Intelligence in Pediatric Cardiovascular Magnetic Resonance Imaging
Addison Gearhart, Scott Anjewierden, Sujatha Buddhe, Animesh Tandon
Abstract
Cardiovascular magnetic resonance (CMR) imaging is essential for the management of congenital heart disease (CHD), due to the ability to perform anatomic and physiologic assessments of patients. However, CMR scans can be time-consuming to perform and analyze, creating roadblocks to broader use of CMR in CHD. Recent publications have shown artificial intelligence (AI) has the potential to increase efficiency, improve image quality, and reduce errors. This review examines the use of AI techniques to improve CMR in CHD, by focusing on deep learning techniques applied to image acquisition and reconstruction, image processing and reporting, clinical use cases, and future directions.