7 papers · 1 filter
Myocardial Strain Drift Correction in Deep Learning Based Ultrasound Tracking
Thierry Judge, Nicolas Duchateau, Andreas Østvik +6
Myocardial strain from echocardiography is a key biomarker for cardiac function. Recent deep learning methods show strong performance for myocardial motion tracking but often lack…
Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?
Thierry Judge, Nicolas Duchateau, Andreas Østvik +13
Speckle tracking echocardiography (STE) is the clinical standard for myocardial strain estimation. Despite good performance on global strain (GLS), its accuracy for regional strain…
Low Complexity Point Tracking of the Myocardium in 2D Echocardiography
Artem Chernyshov, John Nyberg, Vegard Holmstrøm +6
Deep learning methods for point tracking are applicable in 2D echocardiography, but do not yet take advantage of domain specifics that enable extremely fast and efficient configura…
Generative augmentations for improved cardiac ultrasound segmentation using diffusion models
Gilles Van De Vyver, Aksel Try Lenz, Erik Smistad +5
One of the main challenges in current research on segmentation in cardiac ultrasound is the lack of large and varied labeled datasets and the differences in annotation conventions…
Regional quality estimation for echocardiography using deep learning
Gilles Van De Vyver, Svein-Erik Måsøy, Håvard Dalen +7
Automatic estimation of cardiac ultrasound image quality can be beneficial for guiding operators and ensuring the accuracy of clinical measurements. Previous work often fails to di…
Cardiac valve event timing in echocardiography using deep learning and triplane recordings
Benjamin Strandli Fermann, John Nyberg, Espen W. Remme +9
Cardiac valve event timing plays a crucial role when conducting clinical measurements using echocardiography. However, established automated approaches are limited by the need of e…