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Cardiac valve event timing in echocardiography using deep learning and triplane recordings
Benjamin Strandli Fermann, John Nyberg, Espen W. Remme, Jahn Frederik Grue, Hel\'en Grue, Roger H{\aa}land, Lasse Lovstakken, H{\aa}vard Dalen, Bj{\o}rnar Grenne, Svein Arne Aase, Sten Roar Snar, Andreas {\O}stvik
https://arxiv.org/abs…

Cardiac valve event timing in echocardiography using deep learning and triplane recordings
Cardiac valve event timing plays a crucial role when conducting clinical measurements using echocardiography. However, established automated approaches are limited by the need of external electrocardiogram sensors, and manual measurements often rely on timing from different cardiac cycles. Recent methods have applied deep learning to cardiac timing, but they have mainly been restricted to only detecting two key time points, namely end-diastole (ED) and end-systole (ES). In this work, we propose…