"False"
Skip to content
printicon
Main menu hidden.

Image: Mattias Pettersson

Tufve Nyholm Lab

Research group The group is focused on medical imaging using Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET), methods to improve image quality, techniques for segmenting normal and pathological tissues, and the use of imaging data to enhance diagnostics and therapy. We have a particular focus on radiotherapy.

Our research centers on the use of medical imaging primarily in cancer care. This includes research on image enhancement, utilizing AI methods among others, as well as methods for uncertainty estimation of parameters that can be calculated from imaging data, such as blood flow or diffusion. We also focus on methods to segment normal tissue or cancer based on imaging data, using both traditional techniques and AI-based methods.

We place special emphasis on applications in radiotherapy, where imaging data is a critical component in treatment planning. Specifically, we work on improving the understanding of how what is visible on MRI and PET images correlates with underlying tissue properties, as well as studies on how to enhance dose optimization in radiotherapy to reduce the risk of side effects.

Group Members

Anders Garpebring (Associate Professor, Senior Lecturer)

Anders Garpebring is an independent researcher in the group, focusing on MRI, image analysis, and deep learning methods. Anders also works as an MR physicist at Region Västerbotten. He primarily teaches in the medical physics program but also contributes to the medical and radiology nursing programs.

Joakim Jonsson (PhD, Medical Physicist)

Joakim Jonsson is a medical physicist at the University Hospital of Northern Sweden in Umeå. As an expert in medical imaging and radiation therapy, Joakim is involved in most projects and studies conducted within the group. He also leads an independent research line as a principal supervisor in radiation therapy optimization. He teaches in the medical physics and radiology nursing programs.

Kristina Sandgren (PhD, Medical Physicist)

Kristina Sandgren is a medical physicist at the University Hospital of Northern Sweden in Umeå. Her research focuses particularly on hybrid imaging and radiation therapy. In addition to participating in most group projects, she leads an independent research line as a principal supervisor at the intersection of imaging diagnostics, urology, and pathology for prostate cancer. She primarily teaches in the radiology nursing program.

Elin Wallsten (PhD, Medical Physicist)

Elin Wallsten is a medical physicist at the University Hospital of Northern Sweden in Umeå. With a background in nuclear medicine, she now focuses on AI and radiomics. Within the group, Elin leads an independent research line as a principal supervisor on PET imaging in prostate and gynecological cancer and undertakes PostDoc projects on AI and radiomics, primarily related to lymphoma. She is responsible for the technical components of radiology in the medical program at Umeå University.

Attila Simko (PhD, Staff Scientist)

Attila Simko earned his doctorate in AI methods for image processing related to MRI and radiation therapy. In addition to contributing to the group's deep learning projects, Attila leads an independent research line on reproducibility in medical AI applications.

Angsana Keeratijarut Lindberg (PhD, Staff Scientist)

Angsana Lindberg works on the analysis and annotation of histopathological whole-mount prostate sections linked to the PAMP1 and PAMP2 studies.

Josef Lundman (PhD, Medical Physicist, Software engineer)

Josef Lundman is both a medical physicist and software engineer and are involved in several of our projects with his uniqe combination of competences.

Doctoral Students

Erik Nilsson (Licensed Medical Physicist)

Projects related to PAMP studies, risk prediction, and dose planning for prostate cancer.

Josefine Grefve (Licensed Medical Physicist)

Projects related to PAMP studies, diagnostics, and dose planning for prostate cancer.

William Holmlund (Licensed Medical Physicist)

Projects related to PAMP and Hypo-RT-Boost, AI-based delineation of intra-prostatic structures, and treatment uncertainties.

Maryam Zarei

Projects primarily related to PSMA-PET in the PAMP study and PET/MRI and PET/CT in gynecological cancer.

Amanda Östensson (Licensed Medical Physicist)

Projects focusing on treatment optimization for prostate cancer.

Anneli Nilsson (Licensed Medical Physicist)

Projects related to the automation of radiotherapy using AI methods.

Gustav Jönsson (Licensed Medical Physicist)

Projects on automation and uncertainty estimation in segmentation for radiotherapy.

Mikael Bylund

Projects related to the generation of synthetic CT images based on MRI scans.

Max Hellström (Licensed Medical Physicist)

Medical image enhancement and uncertainty prediction

Collaborators at Umeå University

Karin Söderkvist (Oncologist, MD, Phd)

Camilla Thellenberg Karlsson (Oncologist, MD, Phd)

Björn Zackrisson (Oncologist, MD, Prof)

Anders Bergh (Pathologist, MD, Prof)

Sara Strandberg (Radiologist, Nuclear medicine, MD, Phd)

Katrine Riklund (Radiologist, Nuclear medicine, MD, Prof)

Andreas Josefsson (Urologist, MD, Phd)

Pernilla Wikström (Tumor biologist, Prof)

Tommy Löfstedt (Computor scientist, Phd)

Polina Kurtser (Computor scientist, Phd)

Head of research

Tufve Nyholm
Professor, medical physicist
E-mail
Email

Overview

Participating departments and units at Umeå University

Department of Diagnostics and Intervention

Research area

Cancer, Medical technology

External funding

Swedish Cancer Society, Cancerforskningsfonden Norrland, Region Västerbotten, Prostatacancerförbundet

External funding

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.

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.

Publications

Clinical Oncology, Elsevier 2025, Vol. 37
Olsson, C.E.; Krogh, S.L.; Karlsson, Mikael; et al.
Acta Oncologica, MJS Publishing, Medical Journals Sweden 2024, Vol. 63 : 503-510
Zarei, Maryam; Wallstén, Elin; Grefve, Josefine; et al.
Journal of Cerebral Blood Flow and Metabolism, Sage Publications 2024, Vol. 44, (8) : 1343-1351
Björnfot, Cecilia; Eklund, Anders; Larsson, Jenny; et al.
Umeå University medical dissertations, 2264
Simkó, Attila
Magnetic Resonance in Medicine, John Wiley & Sons 2023, Vol. 90, (6) : 2557-2571
Hellström, Max; Löfstedt, Tommy; Garpebring, Anders
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.
Cancerfonden
New Cancer Fund millions for UMU research

Ten projects at Umeå University receive a total of 30 million SEK from the Swedish Cancer Society.

Sophia Harlid sits at a white table and smiles while talking to three researcher who have their backs to the camera.
AI for Images and Genomes, Cancer Research at the Lunch Pitch

Pitches: AI for image processing, understanding breast cancer risk and unravelling plant genome complexity.

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: 2024-12-05