Govil, Sachin
Crabb, Brendan T.
Deng, Yu
Dal Toso, Laura
Puyol-Antón, Esther
Pushparajah, Kuberan
Hegde, Sanjeet
Perry, James C.
Omens, Jeffrey H.
Hsiao, Albert
Young, Alistair A.
McCulloch, Andrew D. http://orcid.org/0000-0002-1708-5675
Funding for this research was provided by:
Foundation for the National Institutes of Health (R01HL121754)
American Heart Association (19AIML35120034)
Saving Tiny Hearts Society
National Heart, Lung, and Blood Institute (T32HL105373)
Health Research Council of New Zealand (17/234)
Wellcome ESPCR Centre for Medical Engineering at King’s College London (WT203148/Z/16/Z)
This article is maintained by: Elsevier
Article Title: A deep learning approach for fully automated cardiac shape modeling in tetralogy of Fallot
Journal Title: Journal of Cardiovascular Magnetic Resonance
CrossRef DOI link to publisher maintained version: https://doi.org/10.1186/s12968-023-00924-1
Content Type: article
Copyright: Copyright © 2023 THE AUTHORS. Published by Elsevier Inc on behalf of the Society for Cardiovascular Magnetic Resonance. Published by Elsevier Inc.