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

Scannell, C.M., Alskaf, E., Sharrack, N. orcid.org/0000-0001-5880-1722 et al. (2 more authors) (2022) 29 AI-AIF: artificial intelligence-based arterial input function correction for quantitative stress perfusion cardiac magnetic resonance. In: Irish Cardiac Society Annual Scientific Meeting & AGM, 06-08 Oct 2022, Cork, Ireland.

Metadata

Item Type: Conference or Workshop Item
Authors/Creators:
Dates:
  • Published: 6 October 2022
  • Published (online): 6 October 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)
Depositing User: Symplectic Publications
Date Deposited: 13 Jun 2024 11:57
Last Modified: 13 Jun 2024 11:57
Published Version: https://heart.bmj.com/content/108/Suppl_3/A25
Status: Published
Publisher: BMJ Publishing Group Ltd and British Cardiovascular Society
Identification Number: 10.1136/heartjnl-2022-ics.29
Open Archives Initiative ID (OAI ID):

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