Echo-E$^3$Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation

Moein Heidari; Afshin Bozorgpour; AmirHossein Zarif-Fakharnia; Wenjin Chen; Dorit Merhof; David J. Foran; Jasmine Grewal; Ilker Hacihaliloglu

arXiv · 2503.17543

Echo-E$^3$Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation

Moein Heidari·Afshin Bozorgpour·AmirHossein Zarif-Fakharnia·Wenjin Chen·Dorit Merhof·David J. Foran·Jasmine Grewal·Ilker Hacihaliloglu

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Abstract

Left ventricular ejection fraction (LVEF) is a primary marker of cardiac function. However, routine estimation from endocardial measurements requires manual delineation at end-diastole (ED) and end-systole (ES), a process that is time-consuming and subject to inter-observer variability. Reliable automation is especially valuable for point-of-care ultrasound (POCUS), where computational resources are limited and acquisition quality varies. We propose Echo-E$^3$Net, an anatomy-guided spatio-temporal network that explicitly embeds cardiac anatomy into LVEF prediction. A dual-phase Endocardial Border Detector (E$^2$CBD) uses phase-specific cross-attention to localize ED/ES endocardial landmarks and produce phase-aware landmark embeddings, while an Endocardial Feature Aggregator (E$^2$FA) fuses these embeddings with global statistical descriptors of deep feature maps to refine EF regression. Training is guided by a lightweight geometric loss that uses ED and ES endocardial landmarks to regularize EF prediction. On EchoNet-Dynamic and a PSAX subset of EchoNet-Pediatric, Echo-E$^3$Net attains competitive performance using only 1.55M parameters and 8.05 GFLOPs, an order-of-magnitude compute reduction versus recent baselines, supporting real-time deployment. Our code is publicly available at https://github.com/moeinheidari7829/Echo-E3Net.

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Moein Heidari, Afshin Bozorgpour, AmirHossein Zarif-Fakharnia, Wenjin Chen, Dorit Merhof, David J. Foran, Jasmine Grewal, Ilker Hacihaliloglu. 2026-09-13. Echo-E$^3$Net: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation. https://arxiv.org/abs/2503.17543

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