Blar i HVL Open på forfatter "Lundervold, Alexander Selvikvåg"

Viser treff 1-11 av 11

    • 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, ...

    • An overview of deep learning in medical imaging focusing on MRI 

      Lundervold, Alexander Selvikvåg; Lundervold, Arvid (Journal article; Peer reviewed, 2018)
      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 ...

    • Association between free-living sleep and memory and attention in healthy adolescents 

      Stefansdóttir, Runa; Gundersen, Hilde; Rögnvaldsdóttir, Vaka; Lundervold, Alexander Selvikvåg; Gestdóttir, Sunna; Gudmundsdóttir, Sigridur Lara; Chen, Kong Y.; Brychta, Robert J.; Johannsson, Erlingur (Peer reviewed; Journal article, 2020)
      In laboratory studies, imposed sleep restriction consistently reduces cognitive performance. However, the association between objectively measured, free-living sleep and cognitive function has not been studied in older ...

    • Automated segmentation of endometrial cancer on MR images using deep learning 

      Hodneland, Erlend; Dybvik, Julie Andrea; Wagner-Larsen, Kari Strøno; Solteszova, Veronika; Munthe-Kaas, Antonella Zanna; 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 (Peer reviewed; Journal article, 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 ...

    • fastMONAI: A low-code deep learning library for medical image analysis 

      Kaliyugarasan, Sathiesh Kumar; Lundervold, Alexander Selvikvåg (Peer reviewed; Journal article, 2023)
      We introduce fastMONAI, an open-source Python-based deep learning library for 3D medical imaging. Drawing upon the strengths of fastai, MONAI, and TorchIO, fastMONAI simplifies the use of advanced techniques for tasks like ...

    • Fully Automatic Whole-Volume Tumor Segmentation in Cervical Cancer 

      Hodneland, Erlend; Kaliyugarasan, Sathiesh Kumar; Wagner-Larsen, Kari Strøno; Lura, Njål Gjærde; Andersen, Erling; Bartsch, Hauke; Smit, Noeska Natasja; Halle, Mari Kyllesø; Krakstad, Camilla; Lundervold, Alexander Selvikvåg; Haldorsen, Ingfrid S. (Peer reviewed; Journal article, 2022)
      Uterine cervical cancer (CC) is the most common gynecologic malignancy worldwide. Whole-volume radiomic profiling from pelvic MRI may yield prognostic markers for tailoring treatment in CC. However, radiomic profiling ...

    • Functional activity level reported by an informant is an early predictor of Alzheimer’s disease 

      Vik, Alexandra; Kocinski, Marek Michal; Rye, Ingrid Karlsen; Lundervold, Astri J.; Lundervold, Alexander Selvikvåg (Peer reviewed; Journal article, 2023)
      Background Loss of autonomy in day-to-day functioning is one of the feared outcomes of Alzheimer’s disease (AD), and relatives may have been worried by subtle behavioral changes in ordinary life situations long before these ...

    • Predicting conversion to Alzheimer’s disease in individuals with Mild Cognitive Impairment using clinically transferable features 

      Rye, Ingrid; Vik, Alexandra; Kocinski, Marek Michal; Lundervold, Alexander Selvikvåg; Lundervold, Astri J. (Peer reviewed; Journal article, 2022)
      Patients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer’s disease (AD). Early identification of underlying neurodegenerative processes is essential to provide treatment before the disease is well ...

    • Pulmonary Nodule Classification in Lung Cancer from 3D Thoracic CT Scans Using fastai and MONAI 

      Kaliyugarasan, Sathiesh Kumar; Lundervold, Arvid; Lundervold, Alexander Selvikvåg (Peer reviewed; Journal article, 2021)
      We construct a convolutional neural network to classify pulmonary nodules as malignant or benign in the context of lung cancer. To construct and train our model, we use our novel extension of the fastai deep learning ...

    • Synthesizing skin lesion images using CycleGANs – a case study 

      Fossen-Romsaas, Sondre; Storm-Johannessen, Adrian; Lundervold, Alexander Selvikvåg (Journal article, 2020)
      Generative adversarial networks (GANs) have seen some success as a way to synthesize training data for supervised machine learning models. In this work, we design two novel approaches for synthetic image generation based ...