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Automatic segmentation of the great arteries for computational hemodynamic assessment

Crossref DOI link: https://doi.org/10.1186/s12968-022-00891-z

Published Print: 2022-01

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Montalt-Tordera, Javier

Pajaziti, Endrit

Jones, Rod

Sauvage, Emilie

Puranik, Rajesh

Singh, Aakansha Ajay Vir

Capelli, Claudio

Steeden, Jennifer

Schievano, Silvia

Muthurangu, Vivek https://orcid.org/0000-0002-4292-6456
Funding

Funding for this research was provided by:

UK Research and Innovation (MR/S032290/1)

Heart Research UK (RG2661/17/20)

British Heart Foundation (NH/18/1/33511, PG/17/6/32797)

Engineering and Physical Sciences Research Council (EP/N02124X/1)

European Research Council (ERC-2017-StG-757923)
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Text and Data Mining valid from 2022-01-01

Text and Data Mining valid from 2022-01-01

Version of Record valid from 2022-11-07
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This article is maintained by: Elsevier

Article Title: Automatic segmentation of the great arteries for computational hemodynamic assessment

Journal Title: Journal of Cardiovascular Magnetic Resonance

CrossRef DOI link to publisher maintained version: https://doi.org/10.1186/s12968-022-00891-z

Content Type: article

Copyright: Copyright © 2022 THE AUTHORS. Published by Elsevier Inc on behalf of the Society for Cardiovascular Magnetic Resonance