dr. J.M. Wolterink (Jelmer)

I obtained my PhD in 2017 at Utrecht University (UMC Utrecht) with a thesis entitled Machine learning based analysis of cardiovascular images. After postdocs in the quantitative image analysis group at UMC Utrecht and Amsterdam UMC, I started as an assistant professor in the Mathematics of Imaging & AI (MIA) group in Twente in March 2020. My research interests are in machine learning for medical image analysis, in particular generative models and geometric deep learning approaches.

I have received a VENI from NWO TTW (2020) to work on Machine learning-based prediction of abdominal aortic aneurysm growth and rupture.

You can read an interview about me and my work on our 'Featured Scientists' website:

Medicine & Life Sciences

# Calcium
# Computed Tomography Angiography
# Coronary Vessels
# Deep Learning

Engineering & Materials Science

# Angiography
# Calcium
# Convolutional Neural Networks
# Deep Learning

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Mathematics of Imaging & AI (MIA)

Thibeau-Sutre, E. , Alblas, D., Buurman, S. , Brune, C. , & Wolterink, J. M. (Accepted/In press). Uncertainty-based quality assurance of carotid artery segmentation. In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE)

van Veldhuizen, W. A., van der Wel, H., Kuipers, H. Y., Kraeima, J., ten Duis, K. , Wolterink, J. M., de Vries, J. P. P. M. , Schuurmann, R. C. L., & IJpma, F. F. A. (2023). Development of a Statistical Shape Model and Assessment of Anatomical Shape Variations in the Hemipelvis. Journal of Clinical Medicine, 12(11), [3767]. https://doi.org/10.3390/jcm12113767

Thibeau-Sutre, E. , Wolterink, J. M., Colliot, O., & Burgos, N. (2023). How Can Data Augmentation Improve Attribution Maps for Disease Subtype Explainability? In O. Colliot, & I. Isgum (Eds.), SPIE Medical Imaging 2023: Image Processing [1246424] SPIE. https://doi.org/10.1117/12.2653809

Suk, J. , Brune, C. , & Wolterink, J. M. (2023). SE(3) symmetry lets graph neural networks learn arterial velocity estimation from small datasets. (pp. 1). ArXiv.org. https://doi.org/10.48550/arXiv.2302.08780

van Veldhuizen, W. A. , Schuurmann, R. C. L., Zuidema, R., Geraedts, A. C. M., IJpma, F. F. A., Kropman, R. H. J., Antoniou, G. A., van Sambeek, M. R. H. M., Balm, R. , Wolterink, J. M., & de Vries, J. P. P. M. (2023). A Statistical Shape Model of Infrarenal Aortic Necks in Patients With and Without Late Type Ia Endoleak After Endovascular Aneurysm Repair. Journal of Endovascular Therapy. https://doi.org/10.1177/15266028221149913

Gerats, B. G. A. , Wolterink, J. M. , & Broeders, I. A. M. J. (2023). 3D human pose estimation in multi-view operating room videos using differentiable camera projections. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 11(4), 1197-1205. https://doi.org/10.1080/21681163.2022.2155580

Suk, J., de Haan, P., Lippe, P. , Brune, C. , & Wolterink, J. M. (2022). Mesh Neural Networks for SE(3)-Equivariant Hemodynamics Estimation on the Artery Wall. (pp. 1). ArXiv.org. https://doi.org/10.48550/arXiv.2212.05023

Gerats, B. G. A. , Wolterink, J. M. , & Broeders, I. A. M. J. (2022). Depth-Supervised NeRF for Multi-View RGB-D Operating Room Images.

Alblas, D. , Brune, C., Yeung, K. K. , & Wolterink, J. M. (2022). Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling. (pp. 1-12).

Alblas, D. , Brune, C., Yeung, K. K. , & Wolterink, J. M. (Accepted/In press). Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling. 79-90. Paper presented at 13th Workshop of Statistical Atlases and Computational Modeling of the Heart, STACOM 2022, Singapore, Singapore. https://doi.org/10.1007/978-3-031-23443-9_8

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+31534895949

j.m.wolterink@utwente.nl

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11), room 2063
Hallenweg 19
7522NH Enschede
The Netherlands

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University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling 2063
P.O. Box 217
7500 AE Enschede
The Netherlands

Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS), Mathematics of Imaging & AI (MIA)

University of Twente Drienerlolaan 5
7522 NB Enschede

+31 (0)53 489 9111
info@utwente.nl
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