Browsing Fakultet for informasjonsteknologi og elektroteknikk (IE) by Author "Aabakken, Lars"
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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. ... -
Improving Automatic Polyp Detection Using CNN by Exploiting Temporal Dependency in Colonoscopy Video
Qadir, Hemin Ali; Balasingham, Ilangko; Sølhusvik, Johannes; Bergsland, Jacob; Aabakken, Lars; Shin, Younghak (Peer reviewed; Journal article, 2019)Automatic polyp detection has been shown to be difficult due to various polyp-like structures in the colon and high interclass variations in polyp size, color, shape, and texture. An efficient method should not only have ... -
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 ...