• Automatic diagnostic tool for predicting cancer grade in bladder cancer patients using deep learning 

      Wetteland, Rune; Engan, Kjersti; Eftestøl, Trygve Christian; Kvikstad, Vebjørn; Janssen, Emiel; Tøssebro, Erlend; Lillesand, Melinda (Peer reviewed; Journal article, 2021-08)
      The most common type of bladder cancer is urothelial carcinoma, which is among the cancer types with the highest recurrence rate and lifetime treatment cost per patient. Diagnosed patients are stratified into risk groups, ...
    • A Multiscale Approach for Whole-Slide Image Segmentation of five Tissue Classes in Urothelial Carcinoma Slides 

      Wetteland, Rune; Engan, Kjersti; Eftestøl, Trygve Christian; Janssen, Emiel; Kvikstad, Vebjørn (Peer reviewed; Journal article, 2020)
      In pathology labs worldwide, we see an increasing number of tissue samples that need to be assessed without the same increase in the number of pathologists. Computational pathology, where digital scans of histological ...
    • Semi-supervised tissue segmentation of histological images 

      Wetteland, Rune; Dalheim, Ove Nicolai; Kvikstad, Vebjørn; Janssen, Emiel; Engan, Kjersti (Peer reviewed; Journal article, 2020-09)
      Supervised learning of convolutional neural networks (CNN) used for image classification and segmentation has produced state-of-the art results, including in many medical image applications. In the medical field, making ...