Deep learning approaches to colorectal cancer diagnosis: a review
Unprecedented breakthroughs in the development of graphical processing systems have
led to great potential for deep learning (DL) algorithms in analyzing visual anatomy from …
led to great potential for deep learning (DL) algorithms in analyzing visual anatomy from …
[HTML][HTML] Detection of elusive polyps using a large-scale artificial intelligence system (with videos)
ABSTRACT Background and Aims Colorectal cancer is a leading cause of death.
Colonoscopy is the criterion standard for detection and removal of precancerous lesions and …
Colonoscopy is the criterion standard for detection and removal of precancerous lesions and …
Blazeneo: Blazing fast polyp segmentation and neoplasm detection
In recent years, computer-aided automatic polyp segmentation and neoplasm detection
have been an emerging topic in medical image analysis, providing valuable support to …
have been an emerging topic in medical image analysis, providing valuable support to …
A comparative study on polyp classification using convolutional neural networks
Colorectal cancer is the third most common cancer diagnosed in both men and women in
the United States. Most colorectal cancers start as a growth on the inner lining of the colon or …
the United States. Most colorectal cancers start as a growth on the inner lining of the colon or …
Computer-aided diagnosis based on convolutional neural network system for colorectal polyp classification: preliminary experience
Abstract Background and Aim: Computer-aided diagnosis (CAD) is becoming a next-
generation tool for the diagnosis of human disease. CAD for colon polyps has been …
generation tool for the diagnosis of human disease. CAD for colon polyps has been …
A self-attention based faster R-CNN for polyp detection from colonoscopy images
At present, the incidence rate of colorectal cancer (CRC) is increasing year by year. It has
always affected people's physical and mental health and quality of life. How to improve the …
always affected people's physical and mental health and quality of life. How to improve the …
Improving automatic polyp detection using CNN by exploiting temporal dependency in colonoscopy video
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 …
in the colon and high interclass variations in polyp size, color, shape, and texture. An …
Endoscopic polyp segmentation using a hybrid 2D/3D CNN
Colonoscopy is the gold standard for early diagnosis and pre-emptive treatment of colorectal
cancer by detecting and removing colonic polyps. Deep learning approaches to polyp …
cancer by detecting and removing colonic polyps. Deep learning approaches to polyp …
Development of a computer-aided detection system for colonoscopy and a publicly accessible large colonoscopy video database (with video)
Background and Aims Artificial intelligence (AI)–assisted polyp detection systems for
colonoscopic use are currently attracting attention because they may reduce the possibility …
colonoscopic use are currently attracting attention because they may reduce the possibility …
Deep learning localizes and identifies polyps in real time with 96% accuracy in screening colonoscopy
G Urban, P Tripathi, T Alkayali, M Mittal, F Jalali… - Gastroenterology, 2018 - Elsevier
Background & Aims The benefit of colonoscopy for colorectal cancer prevention depends on
the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate …
the adenoma detection rate (ADR). The ADR should reflect the adenoma prevalence rate …