Associate Professor

Alexander Selvikvåg Lundervold

Field of work

My main research activities are within machine learning and data analysis, with a particular focus on medical image analysis. I’m co-coordinating a research project on computational medical imaging and machine learning at the Mohn Medical Imaging and Visualization Center, Department of Radiology, Haukeland University Hospital, where I'm also part of the center leadership team. A more detailed description of my research, together with links to my publications, can be found on my homepage:

Courses taught

  • DAT158: Machine learning engineering
  • DAT255: Practical deep learning
  • ELMED219: Artificial intelligence and computational medicine

Research areas

  • Data analysis
  • Computational medicine
  • Machine learning

Research groups


  • A predictive framework based on brain volume trajectories enabling early detection of Alzheimer's disease

    Abolpour Mofrad, Samaneh, Lundervold, Arvid, Lundervold, Alexander Selvikvåg (2021)
  • Cognitive and MRI trajectories for prediction of Alzheimer’s disease

    Abolpour Mofrad, Samaneh, Lundervold, Astri Johansen, Vik, Alexandra, Lundervold, Alexander Selvikvåg (2021)
  • Automated segmentation of endometrial cancer on MR images using deep learning

    Hodneland, Erlend, Dybvik, Julie Andrea, Wagner-Larsen, Kari Strøno, Solteszova, Veronika, Zanna, Antonella, Fasmer, Kristine Eldevik, Krakstad, Camilla, Lundervold, Arvid, Lundervold, Alexander Selvikvåg, Salvesen, Øyvind, Erickson, Bradley J., Haldorsen, Ingfrid S (2021)
  • Synthesizing skin lesion images using CycleGANs – a case study

    Fossen-Romsaas, Sondre, Storm-Johannessen, Adrian, Lundervold, Alexander Selvikvåg (2020)
  • 2D and 3D U-Nets for skull stripping in a large and heterogeneous set of head MRI using fastai

    Kaliyugarasan, Satheshkumar, Kocinski, Marek, Lundervold, Arvid, Lundervold, Alexander Selvikvåg (2020)
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