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Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification

Published Print: 2019-01

Authors

Bratt, Alex

Kim, Jiwon

Pollie, Meridith

Beecy, Ashley N.

Tehrani, Nathan H.

Codella, Noel

Perez-Johnston, Rocio

Palumbo, Maria Chiara

Alakbarli, Javid

Colizza, Wayne

Drexler, Ian R.

Azevedo, Clerio F.

Kim, Raymond J.

Devereux, Richard B.

Weinsaft, Jonathan W. https://orcid.org/0000-0002-8386-0297
Funding

Funding for this research was provided by:

National Institutes of Health (1R01HL128278-01, K23HL102249, NIH 1K23 HL140092-01)
License Information

Text and Data Mining valid from 2019-01-01

Text and Data Mining valid from 2019-01-01

Version of Record valid from 2019-01-07
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This article is maintained by: Elsevier

Article Title: Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification

Journal Title: Journal of Cardiovascular Magnetic Resonance

CrossRef DOI link to publisher maintained version: https://doi.org/10.1186/s12968-018-0509-0

Content Type: article

Copyright: Copyright © 2019 THE AUTHORS. Published by Elsevier Inc on behalf of the Society for Cardiovascular Magnetic Resonance

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