Jelmer M. Wolterink
Orcid: 0000-0001-5505-475X
According to our database1,
Jelmer M. Wolterink
authored at least 67 papers
between 2014 and 2024.
Collaborative distances:
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Bibliography
2024
Generative modeling of living cells with SO(3)-equivariant implicit neural representations.
Medical Image Anal., January, 2024
Brain-Shift: Unsupervised Pseudo-Healthy Brain Synthesis for Novel Biomarker Extraction in Chronic Subdural Hematoma.
CoRR, 2024
Neural Fields for 3D Tracking of Anatomy and Surgical Instruments in Monocular Laparoscopic Video Clips.
CoRR, 2024
CoRR, 2024
LaB-GATr: geometric algebra transformers for large biomedical surface and volume meshes.
CoRR, 2024
2023
Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle.
AI Soc., August, 2023
3D human pose estimation in multi-view operating room videos using differentiable camera projections.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., July, 2023
Quantifying white matter hyperintensity and brain volumes in heterogeneous clinical and low-field portable MRI.
CoRR, 2023
SIRE: scale-invariant, rotation-equivariant estimation of artery orientations using graph neural networks.
CoRR, 2023
CoNeS: Conditional neural fields with shift modulation for multi-sequence MRI translation.
CoRR, 2023
CoRR, 2023
How can data augmentation improve attribution maps for disease subtype explainability.
Proceedings of the Medical Imaging 2023: Image Processing, 2023
Uncertainty-Based Quality Assurance of Carotid Artery Wall Segmentation in Black-Blood MRI.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, 2023
Proceedings of the Predictive Intelligence in Medicine - 6th International Workshop, 2023
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
SE(3) Symmetry Lets Graph Neural Networks Learn Arterial Velocity Estimation from Small Datasets.
Proceedings of the Functional Imaging and Modeling of the Heart, 2023
Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression.
Proceedings of the Functional Imaging and Modeling of the Heart, 2023
2022
Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning.
IEEE Trans. Medical Imaging, 2022
Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall.
CoRR, 2022
Comput. Biol. Medicine, 2022
Proceedings of the Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers, 2022
Deep-learning-based carotid artery vessel wall segmentation in black-blood MRI using anatomical priors.
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2021
Mesh Convolutional Neural Networks for Wall Shear Stress Estimation in 3D Artery Models.
Proceedings of the Statistical Atlases and Computational Models of the Heart. Multi-Disease, Multi-View, and Multi-Center Right Ventricular Segmentation in Cardiac MRI Challenge, 2021
Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis.
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
2020
Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography.
IEEE Trans. Medical Imaging, 2020
Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images.
IEEE Trans. Medical Imaging, 2020
Deep Learning from Dual-Energy Information for Whole-Heart Segmentation in Dual-Energy and Single-Energy Non-Contrast-Enhanced Cardiac CT.
CoRR, 2020
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Exploiting clinically available delineations for CNN-based segmentation in radiotherapy treatment planning.
Proceedings of the Medical Imaging 2020: Image Processing, 2020
2019
A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography.
IEEE Trans. Medical Imaging, 2019
IEEE Trans. Medical Imaging, 2019
Coronary artery centerline extraction in cardiac CT angiography using a CNN-based orientation classifier.
Medical Image Anal., 2019
Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis.
CoRR, 2019
Deep learning analysis of cardiac CT angiography for detection of coronary arteries with functionally significant stenosis.
CoRR, 2019
Improving myocardium segmentation in cardiac CT angiography using spectral information.
Proceedings of the Medical Imaging 2019: Image Processing, 2019
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI.
Proceedings of the Medical Imaging 2019: Image Processing, 2019
Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography.
Proceedings of the Graph Learning in Medical Imaging - First International Workshop, 2019
Adversarial Optimization for Joint Registration and Segmentation in Prostate CT Radiotherapy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Automatic Segmentation of Organs at Risk in Thoracic CT scans by Combining 2D and 3D Convolutional Neural Networks.
Proceedings of the 2019 Challenge on Segmentation of THoracic Organs at Risk in CT Images, 2019
2018
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE Trans. Medical Imaging, 2018
Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis.
Medical Image Anal., 2018
Generative adversarial networks and adversarial methods in biomedical image analysis.
CoRR, 2018
Automatic Detection and Characterization of Coronary Artery Plaque and Stenosis using a Recurrent Convolutional Neural Network in Coronary CT Angiography.
CoRR, 2018
Proceedings of the Medical Imaging 2018: Image Processing, 2018
2017
IEEE Trans. Medical Imaging, 2017
IEEE Trans. Medical Imaging, 2017
Proceedings of the Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS Challenges, 2017
Proceedings of the Simulation and Synthesis in Medical Imaging, 2017
2016
Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks.
Medical Image Anal., 2016
2D image classification for 3D anatomy localization: employing deep convolutional neural networks.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Dilated Convolutional Neural Networks for Cardiovascular MR Segmentation in Congenital Heart Disease.
Proceedings of the Reconstruction, Segmentation, and Analysis of Medical Images, 2016
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2016, 2016
2015
Automatic Coronary Calcium Scoring in Non-Contrast-Enhanced ECG-Triggered Cardiac CT With Ambiguity Detection.
IEEE Trans. Medical Imaging, 2015
Automatic Coronary Calcium Scoring in Cardiac CT Angiography Using Convolutional Neural Networks.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015
Automatic machine learning based prediction of cardiovascular events in lung cancer screening data.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
2014
An automatic machine learning system for coronary calcium scoring in clinical non-contrast enhanced, ECG-triggered cardiac CT.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014