Deep learning supplants visual analysis by experienced operators for the diagnosis of cardiac amyloidosis by cine-CMR

Authors

Philippe Germain, Nouvel Hopital Civil
Armine Vardazaryan, University of Strasbourg
Nicolas Padoy, University of Strasbourg
Aissam Labani, Nouvel Hopital Civil
Catherine Roy, Nouvel Hopital Civil
Thomas Hellmut Schindler, Washington University School of Medicine in St. Louis
Soraya El Ghannudi, Nouvel Hopital Civil

Journal

Diagnostics

Publication Date

12-29-2021

Volume

12

Issue

1

First Page

69

Document Type

Open Access Publication

DOI

10.3390/diagnostics12010069

Rights and Permissions

Germain P, Vardazaryan A, Padoy N, Labani A, Roy C, Schindler TH, El Ghannudi S. Deep Learning Supplants Visual Analysis by Experienced Operators for the Diagnosis of Cardiac Amyloidosis by Cine-CMR. Diagnostics (Basel). 2021 Dec 29;12(1):69. doi: 10.3390/diagnostics12010069. 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Recommended Citation

Germain, Philippe; Vardazaryan, Armine; Padoy, Nicolas; Labani, Aissam; Roy, Catherine; Schindler, Thomas Hellmut; and El Ghannudi, Soraya, "Deep learning supplants visual analysis by experienced operators for the diagnosis of cardiac amyloidosis by cine-CMR." Diagnostics. 12, 1. 69 (2021).
https://digitalcommons.wustl.edu/open_access_pubs/11242