Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography-Reference-Cited by-同舟云学术

Machine Learning-Enabled Fully Automated Assessment of Left Ventricular Volume, Ejection Fraction and Strain: Experience in Pediatric and Young Adult Echocardiography

Published:2022-10-08 Issue: Volume: Page:
ISSN:0172-0643
Container-title:Pediatric Cardiology
language:en
Short-container-title:Pediatr Cardiol

Author:

Li Ling,Homer Paul,Craft Mary,Kutty Shelby,Putschoegl Adam,Marshall Amanda,Danford David,Yetman Anji

Publisher

Springer Science and Business Media LLC

Subject

Cardiology and Cardiovascular Medicine,Pediatrics, Perinatology and Child Health

Link

https://link.springer.com/content/pdf/10.1007/s00246-022-03015-7.pdf

Reference25 articles.

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3. Hoffmann R, Barletta G, Von Bardeleben S et al (2014) Analysis of left ventricular volumes and function: a multicenter comparison of cardiac magnetic resonance imaging, cine ventriculography, and unenhanced and contrast-enhanced two-dimensional and three-dimensional echocardiography. J Am Soc Echocardiogr 27(3):292–301. https://doi.org/10.1016/j.echo.2013.12.005

4. Hoffmann R, von Bardeleben S, ten Cate F et al (2005) Assessment of systolic left ventricular function: a multi-centre comparison of cineventriculography, cardiac magnetic resonance imaging, unenhanced and contrast-enhanced echocardiography. Eur Heart J 26(6):607–616. https://doi.org/10.1093/eurheartj/ehi083

5. Szulik M, Pappas CJ, Jurcut R et al (2011) Clinical validation of a novel speckle-tracking-based ejection fraction assessment method. J Am Soc Echocardiogr 24(10):1092–1100. https://doi.org/10.1016/j.echo.2011.05.004

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