AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance

Scannell, C.M. orcid.org/0000-0001-9240-793X, Alskaf, E., Sharrack, N. orcid.org/0000-0001-5880-1722 et al. (5 more authors) (2023) AI-AIF: artificial intelligence-based arterial input function for quantitative stress perfusion cardiac magnetic resonance. European Heart Journal - Digital Health, 4 (1). pp. 12-21. ISSN 2634-3916

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Item Type: Article
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© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords: Artificial intelligence; Arterial input function; Quantitative myocardial perfusion; Cardiac magnetic resonance
Dates:
  • Published: 31 January 2023
  • Published (online): 7 December 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Biomedical Imaging Science Dept (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 12 Jun 2024 14:42
Last Modified: 12 Jun 2024 14:42
Published Version: https://academic.oup.com/ehjdh/article/4/1/12/6880...
Status: Published
Publisher: Oxford University Press
Identification Number: 10.1093/ehjdh/ztac074
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