Artificial intelligence in cardiovascular imaging: enhancing image analysis and risk stratification-Reference-Cited by-同舟云学术

Artificial intelligence in cardiovascular imaging: enhancing image analysis and risk stratification

Published:2023-08 Issue:1 Volume:5 Page:
ISSN:2513-9878
Container-title:BJR|Open
language:en
Short-container-title:BJR|Open

Author:

Lin Andrew¹²,Pieszko Konrad³⁴,Park Caroline¹,Ignor Katarzyna³,Williams Michelle C⁵,Slomka Piotr⁴,Dey Damini¹

Affiliation:

1. Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA

2. Monash Cardiovascular Research Centre, Victorian Heart Institute, Monash University and MonasHeart, Monash Health, Melbourne, Victoria, Australia

3. Department of Interventional Cardiology, Collegium Medicum, University of Zielona Góra, Zielona Góra, Poland

4. Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA

5. British Heart Foundation Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom

Abstract

In this review, we summarize state-of-the-art artificial intelligence applications for non-invasive cardiovascular imaging modalities including CT, MRI, echocardiography, and nuclear myocardial perfusion imaging.

Publisher

Oxford University Press (OUP)

Subject

General Medicine

Link

https://www.birpublications.org/doi/pdf/10.1259/bjro.20220021

Reference73 articles.

1. Artificial Intelligence in Cardiovascular Imaging

2. Artificial Intelligence in Cardiovascular Imaging for Risk Stratification in Coronary Artery Disease

3. Long-Term Prognosis Associated With Coronary Calcification

4. Deep convolutional neural networks to predict cardiovascular risk from computed tomography

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