Artificial intelligence in cardiovascular CT: Current status and future implications

Andrew Lin; Márton Kolossváry; Manish Motwani; Ivana Išgum; Pál Maurovich-Horvat; Piotr J. Slomka; Damini Dey

doi:10.1016/j.jcct.2021.03.006

Artificial intelligence in cardiovascular CT: Current status and future implications

Andrew Lin, Márton Kolossváry, Manish Motwani, Ivana Išgum, Pál Maurovich-Horvat, Piotr J. Slomka, Damini Dey

Research output: Contribution to journal › Review Article › Other › peer-review

30 Citations (Scopus)

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.

Original language	English
Pages (from-to)	462-469
Number of pages	8
Journal	Journal of Cardiovascular Computed Tomography
Volume	15
Issue number	6
DOIs	https://doi.org/10.1016/j.jcct.2021.03.006
Publication status	Published - 1 Nov 2021
Externally published	Yes

Keywords

Artificial intelligence
Cardiovascular computed tomography
Deep learning
Machine learning

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10.1016/j.jcct.2021.03.006

Cite this

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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.",

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AU - Maurovich-Horvat, Pál

AU - Slomka, Piotr J.

AU - Dey, Damini

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Artificial intelligence in cardiovascular CT: Current status and future implications

Abstract

Keywords

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