Artificial Intelligence in Cardiovascular CT and MR Imaging
Ludovica R. M. Lanzafame,
Giuseppe M. Bucolo,
Giuseppe Muscogiuri,
Sandro Sironi,
Michele Gaeta,
Giorgio Ascenti,
Christian Booz,
Thomas J. Vogl,
Alfredo Blandino,
Silvio Mazziotti,
Tommaso D’Angelo
Affiliations
Ludovica R. M. Lanzafame
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
Giuseppe M. Bucolo
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
Giuseppe Muscogiuri
Department of Radiology, Istituto Auxologico Italiano IRCCS, San Luca Hospital, 20149 Milan, Italy
Sandro Sironi
Department of Medicine and Surgery, University of Milano-Bicocca, 20854 Milan, Italy
Michele Gaeta
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
Giorgio Ascenti
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
Christian Booz
Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, 60590 Frankfurt am Main, Germany
Thomas J. Vogl
Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, 60590 Frankfurt am Main, Germany
Alfredo Blandino
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
Silvio Mazziotti
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
Tommaso D’Angelo
Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy
The technological development of Artificial Intelligence (AI) has grown rapidly in recent years. The applications of AI to cardiovascular imaging are various and could improve the radiologists’ workflow, speeding up acquisition and post-processing time, increasing image quality and diagnostic accuracy. Several studies have already proved AI applications in Coronary Computed Tomography Angiography and Cardiac Magnetic Resonance, including automatic evaluation of calcium score, quantification of coronary stenosis and plaque analysis, or the automatic quantification of heart volumes and myocardial tissue characterization. The aim of this review is to summarize the latest advances in the field of AI applied to cardiovascular CT and MR imaging.
