Artificial Intelligence in Cardiovascular Imaging

Lisa J. Lim; Geoffrey H. Tison; Francesca N. Delling

doi:10.14797/mdcj-16-2-138

Artificial Intelligence in Cardiovascular Imaging

Methodist DeBakey Cardiovascular Journal

Volume 16 (2020): Issue 2

By: Lisa J. Lim, Geoffrey H. Tison and Francesca N. Delling

Open Access

|Apr 2020

Abstract

The number of cardiovascular imaging studies is growing exponentially, and so is the need to improve clinical workflow efficiency and avoid missed diagnoses. With the availability and use of large datasets, artificial intelligence (AI) has the potential to improve patient care at every stage of the imaging chain. Current literature indicates that in the short-term, AI has the capacity to reduce human error and save time in the clinical workflow through automated segmentation of cardiac structures. In the future, AI may expand the informational value of diagnostic images based on images alone or a combination of images and clinical variables, thus facilitating disease detection, prognosis, and decision making. This review describes the role of AI, specifically machine learning, in multimodality imaging, including echocardiography, nuclear imaging, computed tomography, and cardiac magnetic resonance, and highlights current uses of AI as well as potential challenges to its widespread implementation.

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Articles in this issue

DOI: https://doi.org/10.14797/mdcj-16-2-138 | Journal eISSN: 1947-6108

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Language: English

Page range: 138 - 145

Published on: Apr 1, 2020

Published by: Houston Methodist DeBakey Heart & Vascular Center

In partnership with: Paradigm Publishing Services

Keywords:

artificial intelligence,

machine learning,

cardiac imaging

© 2020 Lisa J. Lim, Geoffrey H. Tison, Francesca N. Delling, published by Houston Methodist DeBakey Heart & Vascular Center
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.

Volume 16 (2020): Issue 2