Utilising clinical data to personlaise boundary conditions significantly improves the accuracy of angiography based virtual FFR

Gosling, R. orcid.org/0000-0001-7465-3563, Gunn, E., Wei, H.L. et al. (7 more authors) (2021) Utilising clinical data to personlaise boundary conditions significantly improves the accuracy of angiography based virtual FFR. In: European Heart Journal. ESC Congress 2021, 27-30 Aug 2021, Digital Congress. Oxford University Press , p. 1074.

Metadata

Item Type: Proceedings Paper
Authors/Creators:
Copyright, Publisher and Additional Information:

© The Author(s) 2021. Published on behalf of the European Society of Cardiology.
Dates:
  • Published (online): 14 October 2021
  • Published: October 2021
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
The University of Sheffield > Sheffield Teaching Hospitals
Depositing User: Symplectic Sheffield
Date Deposited: 27 Oct 2022 09:48
Last Modified: 27 Oct 2022 09:48
Status: Published
Publisher: Oxford University Press
Refereed: Yes
Identification Number: 10.1093/eurheartj/ehab724.1074
Related URLs:
Open Archives Initiative ID (OAI ID):

Export

Statistics


CORE (COnnecting REpositories)