| Literature DB >> 33812855 |
Andrew Lin1, Márton Kolossváry2, Manish Motwani3, Ivana Išgum4, Pál Maurovich-Horvat5, Piotr J Slomka6, Damini Dey7.
Abstract
Artificial intelligence (AI) refers to the use of computational techniques to mimic human thought processes and learning capacity. The past decade has seen a rapid proliferation of AI developments for cardiovascular computed tomography (CT). These algorithms aim to increase efficiency, objectivity, and performance in clinical tasks such as image quality improvement, structure segmentation, quantitative measurements, and outcome prediction. By doing so, AI has the potential to streamline clinical workflow, increase interpretative speed and accuracy, and inform subsequent clinical pathways. This review covers state-of-the-art AI techniques in cardiovascular CT and the future role of AI as a clinical support tool.Entities:
Keywords: Artificial intelligence; Cardiovascular computed tomography; Deep learning; Machine learning
Mesh：
Year: 2021 PMID： 33812855 PMCID： PMC8455701 DOI： 10.1016/j.jcct.2021.03.006
Source DB: PubMed Journal: J Cardiovasc Comput Tomogr ISSN： 1876-861X