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:

Expertise

  • Medicine and Dentistry

    • Learning
    • Patient
    • Coronary Artery
    • Computed Tomography Angiography
    • Isotopes of Calcium
  • Biochemistry, Genetics and Molecular Biology

    • Calcium
  • Computer Science

    • Deep Learning Method
    • Segmentation

Organisations

Publications

2025

Towards optimized abdominal aortic aneurysm care: Prediction of sac regression & 3D ultrasound (2025)[Thesis › PhD Thesis - Research external, graduation UT]. University of Twente. van Rijswijk, R. E.https://doi.org/10.3990/1.9789036569606Anatomical characteristics are associated with aneurysm sac regression after endovascular repair (2025)Journal of vascular surgery, 82(6), 2023-2035. van Rijswijk, R. E., Leeuwerke, S. J., Alblas, D., Geelkerken, R. H., Reijnen, M. M., Jebbink, E. G. & Wolterink, J. M.https://doi.org/10.1016/j.jvs.2025.07.045Task based evaluation of sparse view CT reconstruction techniques for intracranial hemorrhage diagnosis using an AI observer model (2025)Scientific reports, 15(1). Article 26002. Tivnan, M., Kikkert, I. D., Wu, D., Yang, K., Wolterink, J. M., Li, Q. & Gupta, R.https://doi.org/10.1038/s41598-025-11089-5Towards personalized trocar placement: Assessment of patient-specific abdominal wall distension due to pneumoperitoneum (2025)Journal of robotic surgery, 19(1). Article 607. Gritter, S. T., Baltus, S. C., Gerats, B. G. A., Tan, C. O., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.1007/s11701-025-02757-9Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior (2025)Computer methods and programs in biomedicine, 271. Article 108958. Suk, J., Nannini, G., Rygiel, P., Brune, C., Pontone, G., Redaelli, A. & Wolterink, J. M.https://doi.org/10.1016/j.cmpb.2025.108958Spatio-temporal artery analysis using geometric deep learning (2025)[Thesis › PhD Thesis - Research UT, graduation UT]. University of Twente. Alblas, D.https://doi.org/10.3990/1.9789036569088Steerable Anatomical Shape Synthesis with Implicit Neural Representations (2025)In Medical Image Computing and Computer Assisted Intervention , MICCAI 2025 - 28th International Conference, 2025, Proceedings (pp. 630-639) (Lecture Notes in Computer Science; Vol. 15962 LNCS). Springer (E-pub ahead of print/First online). de Wilde, B., Rietberg, M. T., Lajoinie, G. & Wolterink, J. M.https://doi.org/10.1007/978-3-032-04947-6_60Consistent View Alignment Improves Foundation Models for 3D Medical Image Segmentation (2025)[Working paper › Preprint]. ArXiv.org. Vaish, P., Meister, F., Heimann, T., Brune, C. & Wolterink, J. M.https://doi.org/10.48550/arXiv.2509.13846Automated surgical workflow recognition in privacy-preserving depth videos of the operating room (2025)Surgical endoscopy, 39(9), 5948-5956. Gerats, B. G. A., Wolterink, J. M. & Broeders, I. A. M. J.https://doi.org/10.1007/s00464-025-12031-6Learning hemodynamic scalar fields on coronary artery meshes: A benchmark of geometric deep learning models (2025)Computers in biology and medicine, 195. Article 110477. Nannini, G., Suk, J., Rygiel, P., Saitta, S., Mariani, L., Maranga, R., Baggiano, A., Pontone, G., Wolterink, J. M. & Redaelli, A.https://doi.org/10.1016/j.compbiomed.2025.110477

Research profiles

Address

University of Twente

Zilverling (building no. 11), room 2063
Hallenweg 19
7522 NH Enschede
Netherlands

Navigate to location

Organisations

Scan the QR code or
Download vCard