Crossmark

Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping

Crossref DOI link: https://doi.org/10.1186/s12968-021-00712-9

Published Print: 2021-03

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

Authors

Ghadimi, Sona

Auger, Daniel A.

Feng, Xue

Sun, Changyu

Meyer, Craig H.

Bilchick, Kenneth C.

Cao, Jie Jane

Scott, Andrew D.

Oshinski, John N.

Ennis, Daniel B.

Epstein, Frederick H. https://orcid.org/0000-0002-1954-1988
Funding

Funding for this research was provided by:

National Heart, Lung, and Blood Institute (R01 HL147104)
License Information

Text and Data Mining valid from 2021-03-01

Text and Data Mining valid from 2021-03-01

Version of Record valid from 2021-03-11
More Information

This article is maintained by: Elsevier

Article Title: Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping

Journal Title: Journal of Cardiovascular Magnetic Resonance

CrossRef DOI link to publisher maintained version: https://doi.org/10.1186/s12968-021-00712-9

Content Type: article

Copyright: Copyright © 2021 THE AUTHORS. Published by Elsevier Inc on behalf of the Society for Cardiovascular Magnetic Resonance

Document is current

Any future updates will be listed below