Artificial Intelligence in Cardiovascular CT and MR Imaging-Reference-Cited by-同舟云学术

Artificial Intelligence in Cardiovascular CT and MR Imaging

Published:2023-02-11 Issue:2 Volume:13 Page:507
ISSN:2075-1729
Container-title:Life
language:en
Short-container-title:Life

Author:

Lanzafame Ludovica R. M.¹^ORCID,Bucolo Giuseppe M.¹^ORCID,Muscogiuri Giuseppe²³,Sironi Sandro³⁴,Gaeta Michele¹,Ascenti Giorgio¹,Booz Christian⁵,Vogl Thomas J.⁵^ORCID,Blandino Alfredo¹,Mazziotti Silvio¹,D’Angelo Tommaso¹⁶^ORCID

Affiliation:

1. Diagnostic and Interventional Radiology Unit, BIOMORF Department, University Hospital Messina, 98124 Messina, Italy

2. Department of Radiology, Istituto Auxologico Italiano IRCCS, San Luca Hospital, 20149 Milan, Italy

3. Department of Medicine and Surgery, University of Milano-Bicocca, 20854 Milan, Italy

4. Department of Radiology, ASST Papa Giovanni XXIII, 24127 Bergamo, Italy

5. Division of Experimental Imaging, Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, 60590 Frankfurt am Main, Germany

6. Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 Rotterdam, The Netherlands

Abstract

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.

Publisher

MDPI AG

Subject

Paleontology,Space and Planetary Science,General Biochemistry, Genetics and Molecular Biology,Ecology, Evolution, Behavior and Systematics

Link

https://www.mdpi.com/2075-1729/13/2/507/pdf

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