• 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 (Journal article, 2020)
      Skull stripping in brain imaging is the removal of the parts of images corresponding to non-brain tissue. Fast and accurate skull stripping is a crucial step for numerous medical brain imaging applications, e.g. registration, ...
    • 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 (Journal article; Peer reviewed, 2021)
      Preoperative MR imaging in endometrial cancer patients provides valuable information on local tumor extent, which routinely guides choice of surgical procedure and adjuvant therapy. Furthermore, whole-volume tumor analyses ...
    • Cognitive and MRI trajectories for prediction of Alzheimer’s disease 

      Abolpour Mofrad, Samaneh; Lundervold, Astri Johansen; Vik, Alexandra; Lundervold, Alexander Selvikvåg (Journal article; Peer reviewed, 2021)
      The concept of Mild Cognitive Impairment (MCI) is used to describe the early stages of Alzheimer’s disease (AD), and identification and treatment before further decline is an important clinical task. We selected longitudinal ...
    • An overview of deep learning in medical imaging focusing on MRI 

      Lundervold, Alexander Selvikvåg; Lundervold, Arvid (Peer reviewed; Journal article, 2018-12-13)
      What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started ...