• Automatic colon polyp detection using region based deep CNN and post learning approaches 

      Shin, Younghak; Qadir, Hemin Ali Qadir; Aabakken, Lars; Bergsland, Jacob; Balasingham, Ilangko (Journal article; Peer reviewed, 2018)
      Automatic image detection of colonic polyps is still an unsolved problem due to the large variation of polyps in terms of shape, texture, size, and color, and the existence of various polyp-like mimics during colonoscopy. ...
    • Polyp detection and segmentation using Mask R-CNN: Does a deeper feature extractor CNN always perform better? 

      Qadir, Hemin Ali Qadir; Shin, Younghak; Solhusvik, Johannes; Bergsland, Jacob; Aabakken, Lars; Balasingham, Ilangko (Journal article; Peer reviewed, 2019)
      Automatic polyp detection and segmentation are highly desirable for colon screening due to polyp miss rate by physicians during colonoscopy, which is about 25%. However, this computerization is still an unsolved problem ...
    • Toward real-time polyp detection using fully CNNs for 2D Gaussian shapes prediction 

      Qadir, Hemin Ali Qadir; Shin, Younghak; Solhusvik, Johannes; Bergsland, Jacob; Aabakken, Lars; Balasingham, Ilangko (Peer reviewed; Journal article, 2020)
      To decrease colon polyp miss-rate during colonoscopy, a real-time detection system with high accuracy is needed. Recently, there have been many efforts to develop models for real-time polyp detection, but work is still ...