AIMC Topic: Colonoscopy

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Multiclassification of Endoscopic Colonoscopy Images Based on Deep Transfer Learning.

Computational and mathematical methods in medicine
With the continuous improvement of human living standards, dietary habits are constantly changing, which brings various bowel problems. Among them, the morbidity and mortality rates of colorectal cancer have maintained a significant upward trend. In ...

A Gastrointestinal Endoscopy Quality Control System Incorporated With Deep Learning Improved Endoscopist Performance in a Pretest and Post-Test Trial.

Clinical and translational gastroenterology
INTRODUCTION: Gastrointestinal endoscopic quality is operator-dependent. To ensure the endoscopy quality, we constructed an endoscopic audit and feedback system named Endo.Adm and evaluated its effect in a form of pretest and posttest trial.

Current status and limitations of artificial intelligence in colonoscopy.

United European gastroenterology journal
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further effor...

A robust real-time deep learning based automatic polyp detection system.

Computers in biology and medicine
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 polyps before they become cancerous. Computer-aided detection systems (...

Enabling Autonomous Colonoscopy Intervention Using a Robotic Endoscope Platform.

IEEE transactions on bio-medical engineering
OBJECTIVE: Robotic endoscopes have the potential to dramatically improve endoscopy procedures, however current attempts remain limited due to mobility and sensing challenges and have yet to offer the full capabilities of traditional tools. Endoscopic...

Unsupervised colonoscopic depth estimation by domain translations with a Lambertian-reflection keeping auxiliary task.

International journal of computer assisted radiology and surgery
PURPOSE: A three-dimensional (3D) structure extraction technique viewed from a two-dimensional image is essential for the development of a computer-aided diagnosis (CAD) system for colonoscopy. However, a straightforward application of existing depth...

Detection of flat colorectal neoplasia by artificial intelligence: A systematic review.

Best practice & research. Clinical gastroenterology
OBJECTIVES: This study review focuses on a deep learning method for the detection of colorectal lesions in colonoscopy and AI support for detecting colorectal neoplasia, especially in flat lesions.

Unsupervised Monocular Depth Estimation for Colonoscope System Using Feedback Network.

Sensors (Basel, Switzerland)
A colonoscopy is a medical examination used to check disease or abnormalities in the large intestine. If necessary, polyps or adenomas would be removed through the scope during a colonoscopy. Colorectal cancer can be prevented through this. However, ...

Prediction of the histology of colorectal neoplasm in white light colonoscopic images using deep learning algorithms.

Scientific reports
The treatment plan of colorectal neoplasm differs based on histology. Although new endoscopic imaging systems have been developed, there are clear diagnostic thresholds and requirements in using them. To overcome these limitations, we trained convolu...