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 does not hold any positions outside the UMC Utrecht.


Side Activities

Not applicable.

Research Output (227)

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.

Application of Supervised Descent Method to MRI Electrical Properties Tomography

Zumbo Sabrina, Mandija Stefano, Meliado Flavio, Van Den Berg Cornelis A.T., Isernia Tommaso, Bevacqua Martina T. 2022,

Advances in MRI based Electrical Properties Tomography:a Comparison between Physics-supported Learning Approaches

Zumbo Sabrina, Mandija Stefano, Meliado Ettore Flavio, Stijnman Peter, Meerbothe Thierry, Van Den Berg Cornelis A.T., Isernia Tommaso, Bevacqua Martina T. 2022,

All research output

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Working at UMC Utrecht





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