5 papers
Reinforcement Learning for Unsupervised Domain Adaptation in Spatio-Temporal Echocardiography Segmentation
Arnaud Judge, Nicolas Duchateau, Thierry Judge +5
Domain adaptation methods aim to bridge the gap between datasets by enabling knowledge transfer across domains, reducing the need for additional expert annotations. However, many a…
Estimation of Segmental Longitudinal Strain in Transesophageal Echocardiography by Deep Learning
Anders Austlid Taskén, Thierry Judge, Erik Andreas Rye Berg +8
Segmental longitudinal strain (SLS) of the left ventricle (LV) is an important prognostic indicator for evaluating regional LV dysfunction, in particular for diagnosing and managin…
Generation of realistic cardiac ultrasound sequences with ground truth motion and speckle decorrelation
Thierry Judge, Nicolas Duchateau, Khuram Faraz +2
Simulated ultrasound image sequences are key for training and validating machine learning algorithms for left ventricular strain estimation. Several simulation pipelines have been…
Fusing Echocardiography Images and Medical Records for Continuous Patient Stratification
Nathan Painchaud, Jérémie Stym-Popper, Pierre-Yves Courand +4
Deep learning enables automatic and robust extraction of cardiac function descriptors from echocardiographic sequences, such as ejection fraction or strain. These descriptors provi…
Uncertainty Propagation for Echocardiography Clinical Metric Estimation via Contour Sampling
Thierry Judge, Olivier Bernard, Woo-Jin Cho Kim +4
Echocardiography plays a fundamental role in the extraction of important clinical parameters (e.g. left ventricular volume and ejection fraction) required to determine the presence…