❭ Research by medical division ❭ Radiology & Nuclear Medicine ❭ Research strategy documents ❭

Research strategy documents:

Short summary of KRN Research strategy 2020-2022 (PDF)

Short summary of KRN Research strategy 2023-2025 (PDF)

 
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Home Research by medical division Radiology & Nuclear Medicine

  • Publications
  • Hepato-Pancreato-Biliary and abdominal transplantation imaging [Syversveen]
  • Computational Radiology & Artificial Intelligence (CRAI) Research Group [Bjørnerud]
  • Neuroimaging Research Group [Ringstad]
  • Musculoskeletal Radiology Research Group [Hellund]
  • Pediatric Radiology Research Group [Ording Müller]
  • Abdominal Radiology [Schulz]
  • MRI Research & Technology [Emblem]
  • Vascular diagnostics and intervention [Haig]
  • CT/X-ray Research & Technology [Jensen]
  • Functional and Molecular Imaging and Therapy [Hernes]
  • Theragnostic Imaging [Stokke]
  • Thoracic imaging and intervention [Aaløkken]
  • Research staff
  • Research strategy documents

Recent publications

Hoffmann-Vold AM, Petelytska L, Fretheim H, Aaløkken TM, Becker MO, Jenssen Bjørkekjær H, Brunborg C, Bruni C, Clarenbach C, Diep PP, Dobrota R, Durheim MT, Elhai M, Frauenfelder T, Huang S, Jordan S, Langballe E, Midtvedt Ø, Mihai C, Mulcaire-Jones E, Pugashetti JV, Sprecher M, Oldham J, Molberg Ø, Khanna D et al. (2025)
Predicting the risk of subsequent progression in patients with systemic sclerosis-associated interstitial lung disease with progression: a multicentre observational cohort study
Lancet Rheumatol (in press)
DOI 10.1016/S2665-9913(25)00026-8, PubMed 40381640

Trøstheim M, Pedersen ML, Leknes S, Hama LM, Roland MN, Lobmaier PP, Solli KK, Weimand BM, Tanum L, Eikemo M (2025)
Reward Sensitivity in Patients Receiving Opioid Agonist and Antagonist Treatment for Opioid Use Disorder: An Observational Study
Biol Psychiatry Cogn Neurosci Neuroimaging (in press)
DOI 10.1016/j.bpsc.2025.04.013, PubMed 40345437

Skattebøl L, Nygaard GO, Leonardsen EH, Kaufmann T, Moridi T, Stawiarz L, Ouellette R, Ineichen BV, Ferreira D, Muehlboeck JS, Beyer MK, Sowa P, Manouchehrinia A, Westman E, Olsson T, Celius EG, Hillert J, Kockum I, Harbo HF, Piehl F, Granberg T, Westlye LT, Høgestøl EA (2025)
Brain age in multiple sclerosis: a study with deep learning and traditional machine learning
Brain Commun, 7 (3), fcaf152
DOI 10.1093/braincomms/fcaf152, PubMed 40337466



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