5 citations · 9 across the 11 of their papers we have counts for
11 papers
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…
EchoTracker2: Enhancing Myocardial Point Tracking by Modeling Local Motion
Md Abulkalam Azad, Vegard Holmstrøm, John Nyberg +4
Myocardial point tracking (MPT) has recently emerged as a promising direction for motion estimation in echocardiography, driven by advances in general-purpose point tracking method…
Lightweight image segmentation for echocardiography
Anders Kjelsrud, Lasse Løvstakken, Erik Smistad +2
Accurate segmentation of the left ventricle in echocardiography can enable fully automatic extraction of clinical measurements such as volumes and ejection fraction. While models c…
Taming Modern Point Tracking for Speckle Tracking Echocardiography via Impartial Motion
Md Abulkalam Azad, John Nyberg, Håvard Dalen +3
Accurate motion estimation for tracking deformable tissues in echocardiography is essential for precise cardiac function measurements. While traditional methods like block matching…
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…
EchoTracker: Advancing Myocardial Point Tracking in Echocardiography
Md Abulkalam Azad, Artem Chernyshov, John Nyberg +5
Tissue tracking in echocardiography is challenging due to the complex cardiac motion and the inherent nature of ultrasound acquisitions. Although optical flow methods are considere…
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…
Towards Robust Cardiac Segmentation using Graph Convolutional Networks
Gilles Van De Vyver, Sarina Thomas, Guy Ben-Yosef +4
Fully automatic cardiac segmentation can be a fast and reproducible method to extract clinical measurements from an echocardiography examination. The U-Net architecture is the curr…