prof. dr. ir. C.A.T. van den Berg

prof. dr. ir. C.A.T. van den Berg

Full Professor
prof. dr. ir. C.A.T. van den Berg
  • Computational Imaging

Research Programs

Strategic Program Cancer



Professor Nico van den Berg is the head of the Computational Imaging group for MRI diagnostics and therapy of the Centre of Image Sciences at the UMC Utrecht. The Computational Imaging group covers all aspects of the MRI workflow for diagnostics and therapy, from first principles modelling and hardware engineering to translating new MRI methods into clinic. For this purpose we draw on expertise and advances from the fields of (MR) physics, mathematics, computing and artificial intelligence.

One important research line is the exploration of next generation techniques to make MRI exams much shorter, reduce patient discomfort and therefore also increase robustness and diagnostic quality. An example of this is the MR-STAT technique developed within the group that can deliver quantitative MRI information based on raw time-domain signals in a fraction of scan time.
Moreover, within my group we have a large research activity on the use of MRI for radiation therapy. This includes 3D motion tracking of moving targets in  MR guided radiation delivery, MRI-only radiation planning and deep learning image processing applications for radiation therapy.

We pay considerable attention to translate our work to actual (clinical) usage in radiotherapy and radiology/ Currently, the group consists of three senior staff members, one computer scientist, four post-docs and eight PhD students.

Prof. Van den Berg is one of the coordinators of the UMC Utrecht accelerator Image guided interventions and the UMCU AI lab for Imaging and Image guided interventions.


Prof. Van den Berg has a 0.9 fte position at the UMC Utrecht. Prof. Van den Berg is co-founder and a minority shareholder of UMCU spin off PrecorDx.  PrecorDx is the winner of the NWO Venture Challenge 2022.


Side Activities

Not applicable.

Research Output (231)

Cartesian vs radial MR-STAT:An efficiency and robustness study

van der Heide Oscar, Sbrizzi Alessandro, van den Berg Cornelis A.T. Jun 2023, In: Magnetic Resonance Imaging. 99 , p. 7-19 13 p.

Synthetic MRI with Magnetic Resonance Spin TomogrAphy in Time-Domain (MR-STAT):Results from a Prospective Cross-Sectional Clinical Trial

Kleinloog Jordi P D, Mandija Stefano, D'Agata Federico, Liu Hongyan, van der Heide Oscar, Koktas Beyza, Dankbaar Jan Willem, Keil Vera C, Vonken Evert-Jan, Jacobs Sarah M, van den Berg Cornelis A T, Hendrikse Jeroen, van der Kolk Anja G, Sbrizzi Alessandro May 2023, In: Journal of Magnetic Resonance Imaging. 57 , p. 1451-1461 11 p.

Efficient performance analysis and optimization of transient-state sequences for multiparametric magnetic resonance imaging

Fuderer Miha, van der Heide Oscar, Liu Hongyan, van den Berg C A T, Sbrizzi Alessandro Mar 2023, In: NMR in Biomedicine. 36 , p. 1-18

Acceleration Strategies for MR-STAT: Achieving High-Resolution Reconstructions on a Desktop PC Within 3 Minutes

Liu Hongyan, van der Heide Oscar, Mandija Stefano, van den Berg Cornelis A. T., Sbrizzi Alessandro Oct 2022, In: IEEE transactions on medical imaging. 41 , p. 2681-2692 12 p.

The future of MRI in radiation therapy:Challenges and opportunities for the MR community

Goodburn Rosie J., Philippens Marielle E.P., Lefebvre Thierry L., Khalifa Aly, Bruijnen Tom, Freedman Joshua N., Waddington David E.J., Younus Eyesha, Aliotta Eric, Meliadò Gabriele, Stanescu Teo, Bano Wajiha, Fatemi-Ardekani Ali, Wetscherek Andreas, Oelfke Uwe, van den Berg Nico, Mason Ralph P., van Houdt Petra J., Balter James M., Gurney-Champion Oliver J. 21 Sep 2022, In: Magnetic Resonance in Medicine. 88 , p. 2592-2608 17 p.

⊥-loss: A symmetric loss function for magnetic resonance imaging reconstruction and image registration with deep learning

Terpstra Maarten, Maspero Matteo, Sbrizzi Alessandro, van den Berg CAT Aug 2022, In: Medical Image Analysis. 80 , p. 1-11

A mask-compatible, radiolucent, 8-channel head and neck receive array for MRI-guided radiotherapy treatments and pre-treatment simulation

Zijlema Stefan Emiel, Breimer Wico, Gosselink Mark W J M, Bruijnen Tom, Arteaga de Castro Catalina S, Tijssen Rob H N, Lagendijk Jan J W, Philippens Marielle E P, Van den Berg Cornelis A T 11 May 2022, In: Physics in medicine and biology. 67 , p. 1-14

A perturbation approach for ultrafast calculation of RF field enhancements near medical implants in MRI

Stijnman Peter R S, Steensma Bart R, van den Berg Cornelis A T, Raaijmakers Alexander J E 10 Mar 2022, In: Scientific Reports. 12 , p. 1-14

Clinical utility of convolutional neural networks for treatment planning in radiotherapy for spinal metastases

Arends Sebastiaan R S, Savenije Mark H F, Eppinga Wietse S C, van der Velden Joanne M, van den Berg Cornelis A T, Verhoeff Joost J C Jan 2022, In: Physics and Imaging in Radiation Oncology. 21 , p. 42-47 6 p.

Uncertainty Assessment for Deep Learning Radiotherapy Applications

van den Berg Cornelis A T, Meliadò Ettore F 2022, In: Seminars in Radiation Oncology. 32 , p. 304-318 15 p.

All research output

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