Blar i NTNU Open på forfatter "Shin, Younghak"
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Abnormal Colon Polyp Image Synthesis Using Conditional Adversarial Networks for Improved Detection Performance
Shin, Younghak; Qadir, Hemin Ali; Balasingham, Ilangko (Journal article; Peer reviewed, 2018)One of the major obstacles in automatic polyp detection during colonoscopy is the lack of labeled polyp training images. In this paper, we propose a framework of conditional adversarial networks to increase the number of ... -
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. ... -
Automatic polyp frame screening using patch based combined feature and dictionary learning
Shin, Younghak; Balasingham, Ilangko (Journal article; Peer reviewed, 2018)Polyps in the colon can potentially become malignant cancer tissues where early detection and removal lead to high survival rate. Certain types of polyps can be difficult to detect even for highly trained physicians. ... -
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 ... -
Simple U-net based synthetic polyp image generation: Polyp to negative and negative to polyp
Qadir, Hemin Ali Qadir; Balasingham, Ilangko; Shin, Younghak (Peer reviewed; Journal article, 2022)Synthetic polyp generation is a good alternative to overcome the privacy problem of medical data and the lack of various polyp samples. In this study, we propose a deep learning-based polyp image generation framework that ... -
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 ...