• Automatic segmentation of human knee anatomy by a convolutional neural network applying a 3D MRI protocol 

      Kulseng, Carl Petter Skaar; Nainamalai, Varatharajan; Grøvik, Endre; Årøen, Asbjørn; Geitung, Jonn Terje; Gjesdal, Kjell-Inge (Peer reviewed; Journal article, 2023)
      Background: To study deep learning segmentation of knee anatomy with 13 anatomical classes by using a magnetic resonance (MR) protocol of four three-dimensional (3D) pulse sequences, and evaluate possible clinical ...
    • DL_Track_US: A python package to analyse muscle ultrasonography images 

      Ritsche, Paul; Seynnes, Olivier Roger; Cronin, Neil J. (Peer reviewed; Journal article, 2023)
      Ultrasonography can be used to assess muscle architectural parameters during static and dynamic conditions. Nevertheless, the analysis of the acquired ultrasonography images presents a major difficulty. Muscle architectural ...
    • Using deep learning to generate synthetic B-mode musculoskeletal ultrasound images 

      Cronin, Neil J.; Finni, Taija; Seynnes, Olivier R. (Peer reviewed; Journal article, 2020)
      Background and objective Deep learning approaches are common in image processing, but often rely on supervised learning, which requires a large volume of training images, usually accompanied by hand-crafted labels. As ...