Real-time polyp detection, localization and segmentation in colonoscopy using deep learning
Computer-aided detection, localization, and segmentation methods can help improve
colonoscopy procedures. Even though many methods have been built to tackle automatic …
colonoscopy procedures. Even though many methods have been built to tackle automatic …
Fully convolutional neural networks for polyp segmentation in colonoscopy
Colorectal cancer (CRC) is one of the most common and deadliest forms of cancer,
accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is …
accounting for nearly 10% of all forms of cancer in the world. Even though colonoscopy is …
Deeppoly: deep learning based polyps segmentation and classification for autonomous colonoscopy examination
Colorectal cancer (CRC) is the third most common cause of cancer-related deaths in the
United States and is anticipated to cause another 52,580 deaths in 2023. The standard …
United States and is anticipated to cause another 52,580 deaths in 2023. The standard …
Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge
Polyps are well-known cancer precursors identified by colonoscopy. However, variability in
their size, appearance, and location makes the detection of polyps challenging. Moreover …
their size, appearance, and location makes the detection of polyps challenging. Moreover …
A robust real-time deep learning based automatic polyp detection system
I Pacal, D Karaboga - Computers in Biology and Medicine, 2021 - Elsevier
Colorectal cancer (CRC) is globally the third most common type of cancer. Colonoscopy is
considered the gold standard in colorectal cancer screening and allows for the removal of …
considered the gold standard in colorectal cancer screening and allows for the removal of …
Real-time detection of colon polyps during colonoscopy using deep learning: systematic validation with four independent datasets
JY Lee, J Jeong, EM Song, C Ha, HJ Lee, JE Koo… - Scientific reports, 2020 - nature.com
We developed and validated a deep-learning algorithm for polyp detection. We used a
YOLOv2 to develop the algorithm for automatic polyp detection on 8,075 images (503 …
YOLOv2 to develop the algorithm for automatic polyp detection on 8,075 images (503 …
Automatic colon polyp detection using region based deep CNN and post learning approaches
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 …
variation of polyps in terms of shape, texture, size, and color, and the existence of various …
Polyp detection and segmentation using mask R-CNN: Does a deeper feature extractor CNN always perform better?
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 …
polyp miss rate by physicians during colonoscopy, which is about 25%. However, this …
A real-time polyp-detection system with clinical application in colonoscopy using deep convolutional neural networks
Colorectal cancer (CRC) is a leading cause of cancer-related deaths worldwide. The best
method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist …
method to prevent CRC is with a colonoscopy. During this procedure, the gastroenterologist …
Polyp detection during colonoscopy using a regression-based convolutional neural network with a tracker
A computer-aided detection (CAD) tool for locating and detecting polyps can help reduce the
chance of missing polyps during colonoscopy. Nevertheless, state-of-the-art algorithms were …
chance of missing polyps during colonoscopy. Nevertheless, state-of-the-art algorithms were …
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