• Evaluating the Impact of High Intensity Interval Training on Axial Psoriatic Arthritis Based on MR Images 

      Chronaiou, Ioanna; Giskeødegård, Guro F.; Neubert, Ales; Hoffmann-Skjøstad, Tamara Viola; Thomsen, Ruth Stoklund; Hoff, Mari; Bathen, Tone Frost; Sitter, Beathe (Journal article; Peer reviewed, 2022)
      High intensity interval training (HIIT) has been shown to benefit patients with psoriatic arthritis (PsA). However, magnetic resonance (MR) imaging has uncovered bone marrow edema (BME) in healthy volunteers after vigorous ...
    • ISIDOG recommendations concerning COVID-19 and pregnancy 

      Donders, Francesca; Lonnee-Hoffmann, Risa; Tsiakalos, Aristotelis; Mendling, Werner; De Oliveira, José Martinez; Judlin, Philippe; Xue, Fengxia; Donders, Gilbert; COVID-19 Guideline Workgroup, ISIDOG (Peer reviewed; Journal article, 2020)
      Providing guidelines to health care workers during a period of rapidly evolving viral pandemic infections is not an easy task, but it is extremely necessary in order to coordinate appropriate action so that all patients ...
    • A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI 

      Sunoqrot, Mohammed R. S.; Selnæs, Kirsten Margrete; Sandsmark, Elise; Nketiah, Gabriel Addio; Zavala-Romero, Olmo; Stoyanova, Radka; Bathen, Tone Frost; Elschot, Mattijs (Journal article; Peer reviewed, 2020)
      Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of magnetic resonance imaging (MRI). Fully automated segmentation ...
    • The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images 

      Sunoqrot, Mohammed R. S.; Selnæs, Kirsten Margrete; Sandsmark, Elise; Langørgen, Sverre; Bertilsson, Helena; Bathen, Tone Frost; Elschot, Mattijs (Peer reviewed; Journal article, 2021)
      Volume of interest segmentation is an essential step in computer-aided detection and diagnosis (CAD) systems. Deep learning (DL)-based methods provide good performance for prostate segmentation, but little is known about ...