J. Wolterink

发表

State-of-the-Art Deep Learning in Cardiovascular Image Analysis.

Bob D. de Vos, G. Litjens, I. Išgum, 2019, JACC. Cardiovascular imaging.

An evaluation of automatic coronary artery calcium scoring methods with cardiac CT using the orCaScore framework.

Bob D. de Vos, L. V. van Vliet, M. Viergever, 2016, Medical physics.

Machine Learning for Assessment of Coronary Artery Disease in Cardiac CT: A Survey

I. Išgum, T. Leiner, J. Wolterink, 2019, Front. Cardiovasc. Med..

AI-based quantification of planned radiotherapy dose to cardiac structures and coronary arteries in breast cancer patients.

M. Viergever, H. Verkooijen, I. Išgum, 2021, International journal of radiation oncology, biology, physics.

Knowledge-based and deep learning-based automated chest wall segmentation in Magnetic Resonance Images of extremely dense breasts.

I. Išgum, K. Gilhuijs, W. Veldhuis, 2019, Medical physics.

Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT

D. Dey, D. Berman, P. Slomka, 2017, Journal of Nuclear Cardiology.

Six months vitamin K treatment does not affect systemic arterial calcification or bone mineral density in diabetes mellitus 2

P. D. de Jong, Y. T. van der Schouw, N. Lessmann, 2020, European Journal of Nutrition.

The effect of menaquinone-7 supplementation on vascular calcification in patients with diabetes: a randomized, double-blind, placebo-controlled trial

L. Schurgers, R. Slart, J. Beulens, 2019, The American journal of clinical nutrition.

Deep Learning-Based Intraoperative Stent Graft Segmentation on Completion Digital Subtraction Angiography During Endovascular Aneurysm Repair.

K. Yeung, J. Wolterink, A. Hoksbergen, 2022, Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists.

Vascular uptake on 18F-sodium fluoride positron emission tomography: precursor of vascular calcification?

W. Mali, W. Spiering, P. D. de Jong, 2020, Journal of Nuclear Cardiology.

Determinants of 18F-NaF uptake in femoral arteries in patients with type 2 diabetes mellitus

P. D. de Jong, R. Takx, J. Beulens, 2020, Journal of Nuclear Cardiology.

Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling

C. Brune, K. Yeung, J. Wolterink, 2022, STACOM@MICCAI.

Etidronate halts systemic arterial calcification in pseudoxanthoma elasticum.

I. Išgum, W. Mali, W. Spiering, 2019, Atherosclerosis.

CLINICAL INVESTIGATION AI-Based Quantiﬁcation of Planned Radiation Therapy Dose to Cardiac Structures and Coronary Arteries in Patients With Breast Cancer

Sanne G. M. van Velzen, M. Viergever, H. Verkooijen, 2022 .

3D human pose estimation in multi-view operating room videos using differentiable camera projections

I. Broeders, J. Wolterink, Beerend Gerats, 2022, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization.

A Comparative Study of Graph Neural Networks for Shape Classification in Neuroimaging

Angelica I. Avilés-Rivero, Ben Glocker, E. Bekkers, 2022, ArXiv.

Implicit Neural Representations for Deformable Image Registration

C. Brune, J. Wolterink, Jesse C. Zwienenberg, 2022, MIDL.

ConvNet-Based Localization of Anatomical Structures in 3-D Medical Images

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2017, IEEE Transactions on Medical Imaging.

Generative Adversarial Networks for Noise Reduction in Low-Dose CT

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2017, IEEE Transactions on Medical Imaging.

Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2016, Medical Image Anal..

Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?

Xin Yang, Pheng-Ann Heng, Peter M. Full, 2018, IEEE Transactions on Medical Imaging.

Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression

C. Brune, K. Yeung, J. Wolterink, 2023, FIMH.

Deep-learning-based carotid artery vessel wall segmentation in black-blood MRI using anatomical priors pdf

Christoph Brune, Jelmer M. Wolterink, Dieuwertje Alblas, 2021, Medical Imaging.

Deep MR to CT Synthesis Using Unpaired Data

Jelmer M. Wolterink, Ivana Išgum, Mark H. F. Savenije, 2017, SASHIMI@MICCAI.

Embedding artificial intelligence in society: looking beyond the EU AI master plan using the culture cycle

F. Nex, B. Veldkamp, R. Zurita-Milla, 2022, AI & SOCIETY.

Submillisievert coronary calcium quantification using model-based iterative reconstruction: A within-patient analysis.

Tim Leiner, Ivana Išgum, Jelmer M Wolterink, 2016, European journal of radiology.

Commonly available hematological biomarkers are associated with the extent of coronary calcifications.

I. Išgum, T. Leiner, P. D. de Jong, 2018, Atherosclerosis.

Automatic Segmentation and Disease Classification Using Cardiac Cine MR Images

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2017, STACOM@MICCAI.

A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2018, IEEE Transactions on Medical Imaging.

Automatic Online Quality Control of Synthetic CTs

Jelmer M. Wolterink, Ivana Isgum, Louis D. van Harten, 2019, Medical Imaging: Image Processing.

Simulation and Synthesis in Medical Imaging: 5th International Workshop, SASHIMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

Ninon Burgos, David Svoboda, Jelmer M. Wolterink, 2020, SASHIMI@MICCAI.

Super-Resolved Microbubble Localization in Single-Channel Ultrasound RF Signals Using Deep Learning

H. Delingette, M. Versluis, C. Brune, 2022, IEEE Transactions on Medical Imaging.

Direct Automatic Coronary Calcium Scoring in Cardiac and Chest CT

Nikolas Lessmann, Tim Leiner, Jelmer M. Wolterink, 2019, IEEE Transactions on Medical Imaging.

Deep Learning for Multi-Task Medical Image Segmentation in Multiple Modalities pdf

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2016, MICCAI.

Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography

Tim Leiner, Jelmer M. Wolterink, Ivana Isgum, 2019, GLMI@MICCAI.

Coronary artery centerline extraction in cardiac CT angiography using a CNN‐based orientation classifier

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2018, Medical Image Anal..

Deep Learning Analysis of Coronary Arteries in Cardiac CT Angiography for Detection of Patients Requiring Invasive Coronary Angiography

Tim Leiner, Majd Zreik, Max A Viergever, 2019, IEEE Transactions on Medical Imaging.

Deep learning analysis of the myocardium in coronary CT angiography for identification of patients with functionally significant coronary artery stenosis

Max A. Viergever, Nikolas Lessmann, Tim Leiner, 2017, Medical Image Anal..

Automatic Coronary Calcium Scoring in Non-Contrast-Enhanced ECG-Triggered Cardiac CT With Ambiguity Detection

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2015, IEEE Transactions on Medical Imaging.

Generative Adversarial Networks: A Primer for Radiologists.

I. Išgum, T. Leiner, A. Mukhopadhyay, 2021, Radiographics : a review publication of the Radiological Society of North America, Inc.

Automatic Coronary Calcium Scoring in Cardiac CT Angiography Using Convolutional Neural Networks

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2015, MICCAI.

Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images

Paul A. M. Smeets, Tim Leiner, Max A. Viergever, 2020, IEEE Transactions on Medical Imaging.

Anatomy-aided deep learning for medical image segmentation: a review

C. Brune, R. Veldhuis, J. Wolterink, 2021, Physics in medicine and biology.

SE(3) symmetry lets graph neural networks learn arterial velocity estimation from small datasets

C. Brune, J. Wolterink, J. Suk, 2023, FIMH.

Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall

C. Brune, P. D. Haan, Phillip Lippe, 2022, ArXiv.

MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network.

Jelmer M. Wolterink, Ivana Išgum, Anna M. Dinkla, 2018, International journal of radiation oncology, biology, physics.

Development of a Statistical Shape Model and Assessment of Anatomical Shape Variations in the Hemipelvis

J. Kraeima, J. Wolterink, F. IJpma, 2023, Journal of clinical medicine.

A Multi-Stain Breast Cancer Histological Whole-Slide-Image Data Set from Routine Diagnostics

Chandler D. Gatenbee, R. Greiner, L. Latonen, 2023, Scientific data.

Cardiovascular Diseases

I. Išgum, T. Leiner, W. Veldhuis, 2019, Artificial Intelligence in Medical Imaging.

Improving Myocardium Segmentation in Cardiac CT Angiography using Spectral Information pdf

Tim Leiner, Jelmer M. Wolterink, Majd Zreik, 2018, Medical Imaging: Image Processing.

Combined analysis of coronary arteries and the left ventricular myocardium in cardiac CT angiography for detection of patients with functionally significant stenosis pdf

Max A. Viergever, Tim Leiner, Jelmer M. Wolterink, 2019, Medical Imaging.

Generative adversarial networks and adversarial methods in biomedical image analysis pdf

Konstantinos Kamnitsas, Christian Ledig, Jelmer M. Wolterink, 2018, ArXiv.

Depth-Supervised NeRF for Multi-View RGB-D Operating Room Images

I. Broeders, J. Wolterink, Beerend G. A. Gerats, 2022, ArXiv.

Generative modeling of living cells with SO(3)-equivariant implicit neural representations

J. Wolterink, V. Ulman, Tereza Nečasová, 2023, ArXiv.

Implicit Neural Representations for Generative Modeling of Living Cell Shapes

J. Wolterink, D. Svoboda, J. Suk, 2022, MICCAI.

2D image classification for 3D anatomy localization: employing deep convolutional neural networks

Max A. Viergever, Pim A. de Jong, Jelmer M. Wolterink, 2016, SPIE Medical Imaging.

Deep learning analysis of cardiac CT angiography for detection of coronary arteries with functionally significant stenosis

M. Viergever, I. Išgum, M. Voskuil, 2019, ArXiv.

Dynamic Depth-Supervised NeRF for Multi-view RGB-D Operating Room Videos

I. Broeders, J. Wolterink, Beerend G. A. Gerats, 2022, PRIME@MICCAI.

Adversarial optimization for joint registration and segmentation in prostate CT radiotherapy pdf

Marius Staring, Jelmer M. Wolterink, Mohamed S. Elmahdy, 2019, MICCAI.

Graph attention networks for segment labeling in coronary artery trees

Jelmer M. Wolterink, Nils Planken, Ivana Išgum, 2021, Medical Imaging.

Deep learning: Generative adversarial networks and adversarial methods

Konstantinos Kamnitsas, Christian Ledig, Jelmer M. Wolterink, 2019 .

A Statistical Shape Model of the Morphological Variation of the Infrarenal Abdominal Aortic Aneurysm Neck

G. Antoniou, J. Wolterink, F. IJpma, 2022, Journal of clinical medicine.

A Statistical Shape Model of Infrarenal Aortic Necks in Patients With and Without Late Type Ia Endoleak After Endovascular Aneurysm Repair.

G. Antoniou, R. Balm, J. Wolterink, 2023, Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists.

CoNeS: Conditional neural fields with shift modulation for multi-sequence MRI translation

Q. Tao, J. Wolterink, Yunjie Chen, 2023, Machine Learning for Biomedical Imaging.

Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI

Jelmer M. Wolterink, Ivana Išgum, Bob D. de Vos, 2018, Medical Imaging: Image Processing.

Dilated Convolutional Neural Networks for Cardiovascular MR Segmentation in Congenital Heart Disease

Tim Leiner, Ivana Išgum, Jelmer M. Wolterink, 2016, RAMBO+HVSMR@MICCAI.

Deep learning-based whole-heart segmentation in 4D contrast-enhanced cardiac CT

M. Viergever, I. Išgum, B. Bouma, 2021, Comput. Biol. Medicine.

Automatic whole-heart segmentation in 4D TAVI treatment planning CT

Jelmer M. Wolterink, Ivana Išgum, Jan Baan, 2021, Medical Imaging.

Exploiting Clinically Available Delineations for CNN-based Segmentation in Radiotherapy Treatment Planning

Jelmer M. Wolterink, Ivana Isgum, Louis D. van Harten, 2019, Medical Imaging: Image Processing.