Automated assessment of COVID-19 reporting and data system and chest CT severity scores in patients suspected of having COVID-19 using artificial intelligence N Lessmann, CI Sánchez, L Beenen, LH Boulogne, M Brink, E Calli, ... Radiology 298 (1), E18-E28, 2021 | 115 | 2021 |
Automated assessment of CO-RADS and chest CT severity scores in patients with suspected COVID-19 using artificial intelligence N Lessmann, CI Sánchez, L Beenen, LH Boulogne, M Brink, E Calli, ... Radiology, 2020 | 71 | 2020 |
openPSTD: The open source pseudospectral time-domain method for acoustic propagation M Hornikx, T Krijnen, L van Harten Computer Physics Communications 203, 298-308, 2016 | 42 | 2016 |
Knowledge distillation with ensembles of convolutional neural networks for medical image segmentation JMH Noothout, N Lessmann, MC Van Eede, LD van Harten, ... Journal of Medical Imaging 9 (5), 052407-052407, 2022 | 22 | 2022 |
Untangling and segmenting the small intestine in 3D cine-MRI using deep learning LD van Harten, CS de Jonge, KJ Beek, J Stoker, I Išgum Medical image analysis 78, 102386, 2022 | 19 | 2022 |
Necessity of fault tolerance techniques in Xilinx Kintex 7 FPGA devices for space missions: A case study L van Harten, R Jordans, H Pourshaghaghi 2017 Euromicro Conference on Digital System Design (DSD), 299-306, 2017 | 17 | 2017 |
Robust deformable image registration using cycle-consistent implicit representations LD Van Harten, J Stoker, I Išgum IEEE Transactions on Medical Imaging, 2023 | 16 | 2023 |
Automatic Segmentation of Organs at Risk in Thoracic CT scans by Combining 2D and 3D Convolutional Neural Networks LD van Harten, JMH Noothout, JJC Verhoeff, JM Wolterink, I Išgum | 16 | 2019 |
Determining the necessity of fault tolerance techniques in FPGA devices for space missions LD van Harten, M Mousavi, R Jordans, HR Pourshaghaghi Microprocessors and Microsystems 63, 1-10, 2018 | 14 | 2018 |
Deformable Image Registration with Geometry-informed Implicit Neural Representations L van Harten, RLM Van Herten, J Stoker, I Isgum Medical Imaging with Deep Learning, 2023 | 13 | 2023 |
Automatic online quality control of synthetic CTs LD van Harten, JM Wolterink, JJC Verhoeff, I Išgum Medical Imaging 2020: Image Processing 11313, 399-405, 2020 | 10 | 2020 |
PR3: A system For radio-interferometry and radiation measurement on sounding rockets M Wijtvliet, B Pont, C Brinkerink, HR Pourshaghaghi, R Jordans, ... Microprocessors and Microsystems 77, 103163, 2020 | 7 | 2020 |
Untangling the Small Intestine in 3D cine-MRI using Deep Stochastic Tracking L van Harten, C de Jonge, J Stoker, I Isgum | 4 | 2021 |
Quantitative analysis of small intestinal motility in 3D cine‐MRI using centerline‐aware motion estimation LD van Harten, CS de Jonge, F Struik, J Stoker, I Išgum Journal of Magnetic Resonance Imaging, 2024 | 1 | 2024 |
Motion analysis in 4D MRI of the small intestine using neural networks LD van Harten | | 2024 |
REINDIR: Repeated Embedding Infusion for Neural Deformable Image Registration L van Harten, RLM Van Herten, I Isgum Medical Imaging with Deep Learning, 2024 | | 2024 |
Generative Adversarial Networks for Coronary CT Angiography Acquisition Protocol Correction with Explicit Attenuation Constraints RLM Van Herten, L van Harten, N Planken, I Isgum Medical Imaging with Deep Learning, 2023 | | 2023 |
Exploiting clinically available delineations for CNN-based segmentation in radiotherapy treatment planning LD van Harten, JM Wolterink, JJC Verhoeff, I Išgum Medical Imaging 2020: Image Processing 11313, 331-337, 2020 | | 2020 |