Explicit and automatic ejection fraction assessment on 2D cardiac ultrasound with a deep learning-based approach.
Journal:
Computers in biology and medicine
Published Date:
May 17, 2022
Abstract
BACKGROUND: Ejection fraction (EF) is a key parameter for assessing cardiovascular functions in cardiac ultrasound, but its manual assessment is time-consuming and subject to high inter and intra-observer variability. Deep learning-based methods have the potential to perform accurate fully automatic EF predictions but suffer from a lack of explainability and interpretability. This study proposes a fully automatic method to reliably and explicitly evaluate the biplane left ventricular EF on 2D echocardiography following the recommended modified Simpson's rule.