AI RESEARCH
Echo-E$^3$Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation
arXiv CS.CV
•
ArXi:2503.17543v3 Announce Type: replace-cross Objective To develop a robust and computationally efficient deep learning model for automated left ventricular ejection fraction (LVEF) estimation from echocardiography videos that is suitable for real-time point-of-care ultrasound (POCUS) deployment. Methods We propose Echo-E$^3$Net, an endocardial spatio-temporal network that explicitly incorporates cardiac anatomy into LVEF prediction.