Publications
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Deep neural network-based clustering of deformation curves reveals novel disease features in PLN pathogenic variant carriers KU Leuven
Echocardiographic deformation curves provide detailed information on myocardial function. Deep neural networks (DNNs) may enable automated detection of disease features in deformation curves, and improve the clinical assessment of these curves. We aimed to investigate whether an explainable DNN-based pipeline can be used to detect and visualize disease features in echocardiographic deformation curves of phospholamban (PLN) p.Arg14del variant ...
Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping KU Leuven
Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement biases specific to each protocol. We show how dynamic time warping and partial least squares ...
First in vivo proof-of-concept of nanodroplet-mediated ultrasound-based proton range verification KU Leuven
Use of 3D anatomical models in mock circulatory loops for cardiac medical device testing KU Leuven
INTRODUCTION: Mock circulatory loops (MCLs) are mechanical representations of the cardiovascular system largely used to test the hemodynamic performance of cardiovascular medical devices (MD). Thanks to 3 dimensional (3D) printing technologies, MCLs can nowadays also incorporate anatomical models so to offer enhanced testing capabilities. The aim of this review is to provide an overview on MCLs and to discuss the recent developments of 3D ...
MITEA: A dataset for machine learning segmentation of the left ventricle in 3D echocardiography using subject-specific labels from cardiac magnetic resonance imaging KU Leuven
Segmentation of the left ventricle (LV) in echocardiography is an important task for the quantification of volume and mass in heart disease. Continuing advances in echocardiography have extended imaging capabilities into the 3D domain, subsequently overcoming the geometric assumptions associated with conventional 2D acquisitions. Nevertheless, the analysis of 3D echocardiography (3DE) poses several challenges associated with limited spatial ...