Automatic estimation of the ejection fraction from diastole and systole ultrasound images by a simplified end-to-end U-Net neural network-Reference-Cited by-同舟云学术

Automatic estimation of the ejection fraction from diastole and systole ultrasound images by a simplified end-to-end U-Net neural network

Published:2023-11-15 Issue: Volume: Page:1-5
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Container-title:2023 19th International Symposium on Medical Information Processing and Analysis (SIPAIM)
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Author:

Toro-Quitian Leonard¹,Torres Juan Camilo²,Carrera-Pinzón Andrés Felipe¹,Gutiérrez-Carvajal R.E³,Guerrero Marcela Iregui⁴,Cruz-Roa Angel²,Davila Carlos Órtiz¹,Romero Eduardo¹

Affiliation:

1. Universidad Nacional de Colombia,CIM@LAB,Bogotá,Colombia

2. Universidad de los Llanos,GITECX & Adalab,Villavicencio,Colombia

3. Tecnologico de Monterrey,Mexico City,Mexico

4. Universidad Militar Nueva Granada,ACCEDER,Bogotá,Colombia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10373395/10373414/10373544.pdf?arnumber=10373544

Reference11 articles.

1. Cardiovascular Diseases (CVDs)

2. The growing role of echocardiography in interventional cardiology: The present and the future

3. Universal definition and classification of heart failure: a report of the Heart Failure Society of America, Heart Failure Association of the European Society of Cardiology, Japanese Heart Failure Society and Writing Committee of the Universal Definition of Heart Failure

4. Left Ventricular Ejection Fraction

5. EchoGNN: Explainable Ejection Fraction Estimation with Graph Neural Networks

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