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Image: Mattias Pettersson

Tufve Nyholm Lab

Research group Magnetic resonance imaging both for planning radiation therapy and for early estimation of treatment response.

Currently, my main area of research is MRI in cancer care, including both integration of MR in the radiotherapy workflow and use of MR techniques for early assessment of treatment response. The focus towards AI solutions is growing, both as a research tool and in a translational setting for future integration in clinical workflows.

PhD in Radiation Physics in 2009 and professor in 2018. The PhD thesis was focused on algorithms for dose calculations and quality assurance aspects on external radiotherapy. This work is partly the basis for the EqualDose software. My focus has since shifted towards imaging, AI and advancing treatment strategies. Prostate cancer is a focus area where we work towards better understanding of MR and PET data in order to optimize radiotherapy for the individual patient. 

The work with image analysis has lead to the development of the research tool Hero, previously Mice toolkit, which has resulted in a spin-off company and is used for research on most continents. 

Head of research

Tufve Nyholm
Professor, medical physicist


Participating departments and units at Umeå University

Department of Radiation Sciences

Research area

Cancer, Medical technology
Thesis about resource efficient automatic segmentation of medical images

How to improve resource efficiency in medical images by automatic segmentation is focus for a doctoral thesis.

Anders wants to reduce debris and interference in X-rays

Anders Garpebring wants to get sharper and clearer results from images of cancerous tumors, with help of AI.


IEEE Transactions on Medical Imaging, IEEE 2022, Vol. 41, (6) : 1320-1330
Vu, Minh Hoang; Norman, Gabriella; Nyholm, Tufve; et al.
Zeitschrift für Medizinische Physik, Elsevier 2021, Vol. 31, (1) : 78-88
Zimmermann, Lukas; Buschmann, Martin; Herrmann, Harald; et al.
Physica medica (Testo stampato), Elsevier 2021, Vol. 88 : 218-225
Andersson, Jonas; Nyholm, Tufve; Ceberg, Crister; et al.
Journal of Cerebral Blood Flow and Metabolism, Sage Publications 2021, Vol. 41, (10) : 2769-2777
Björnfot, Cecilia; Garpebring, Anders; Qvarlander, Sara; et al.
Frontiers in Signal Processing, Frontiers Media S.A. 2021, Vol. 1
Wang, Jianfeng; Garpebring, Anders; Brynolfsson, Patrik; et al.
Journal of Applied Clinical Medical Physics, John Wiley & Sons 2021, Vol. 22, (12) : 51-63
Jamtheim Gustafsson, Christian; Lempart, Michael; Swärd, Johan; et al.
Medical physics (Lancaster), John Wiley & Sons 2021, Vol. 48, (7) : e671-e696
Andersson, Jonas; Bednarek, Daniel R.; Bolch, Wesley; et al.
Radiotherapy and Oncology, Elsevier 2021, Vol. 156 : 80-94
Combs, Stephanie E.; Baumert, Brigitta G.; Bendszus, Martin; et al.
IEEE Transactions on Medical Imaging, IEEE 2020, Vol. 39, (9) : 2856-2868
Vu, Minh Hoang; Löfstedt, Tommy; Nyholm, Tufve; et al.
Physics in Medicine and Biology, Institute of Physics (IOP) 2020, Vol. 65, (22)
Löfstedt, Tommy; Hellström, Max; Bylund, Mikael; et al.
Anders wants to reduce debris and interference in X-rays

Anders Garpebring wants to get sharper and clearer results from images of cancerous tumors, with help of AI.

Latest update: 2022-04-20