122 citations · 220 across the 9 of their papers we have counts for
22 papers
A Comparative Study of Graph Neural Networks for Shape Classification in Neuroimaging
Nairouz Shehata, Wulfie Bain, Ben Glocker
Graph neural networks have emerged as a promising approach for the analysis of non-Euclidean data such as meshes. In medical imaging, mesh-like data plays an important role for mod…
Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning
Nathan Blanken, Jelmer M. Wolterink, Hervé Delingette +3
Recently, super-resolution ultrasound imaging with ultrasound localization microscopy (ULM) has received much attention. However, ULM relies on low concentrations of microbubbles i…
Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT
Steffen Bruns, Jelmer M. Wolterink, Richard A. P. Takx +5
Deep learning-based whole-heart segmentation in coronary CT angiography (CCTA) allows the extraction of quantitative imaging measures for cardiovascular risk prediction. Automatic…
Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images
Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink +6
In this study, we propose a fast and accurate method to automatically localize anatomical landmarks in medical images. We employ a global-to-local localization approach using fully…
Automatic Online Quality Control of Synthetic CTs
Louis D. van Harten, Jelmer M. Wolterink, Joost J. C. Verhoeff +1
Accurate MR-to-CT synthesis is a requirement for MR-only workflows in radiotherapy (RT) treatment planning. In recent years, deep learning-based approaches have shown impressive re…
Exploiting Clinically Available Delineations for CNN-based Segmentation in Radiotherapy Treatment Planning
Louis D. van Harten, Jelmer M. Wolterink, Joost J. C. Verhoeff +1
Convolutional neural networks (CNNs) have been widely and successfully used for medical image segmentation. However, CNNs are typically considered to require large numbers of dedic…