AIMC Topic: Colonoscopy

Clear Filters Showing 301 to 310 of 353 articles

A Deep Learning Model for Classifying Histological Types of Colorectal Polyps.

Studies in health technology and informatics
In this study a deep learning architecture based on a convolutional neural network has been evaluated for the classification of white light images of colorectal polyps acquired during the process of a colonoscopy, to estimate the accuracy of the opti...

Application of Deep Learning Models to Improve Ulcerative Colitis Endoscopic Disease Activity Scoring Under Multiple Scoring Systems.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Lack of clinical validation and inter-observer variability are two limitations of endoscopic assessment and scoring of disease severity in patients with ulcerative colitis [UC]. We developed a deep learning [DL] model to improve,...

Effects of ai-assisted colonoscopy on adenoma miss rate/adenoma detection rate: A protocol for systematic review and meta-analysis.

Medicine
BACKGROUND: Colonoscopy can detect colorectal adenomas and reduce the incidence of colorectal cancer, but there are still many missing diagnoses. Artificial intelligence-assisted colonoscopy (AIAC) can effectively reduce the rate of missed diagnosis ...

Robotic, self-propelled, self-steerable, and disposable colonoscopes: Reality or pipe dream? A state of the art review.

World journal of gastroenterology
Robotic colonoscopes could potentially provide a comfortable, less painful and safer alternative to standard colonoscopy. Recent exciting developments in this field are pushing the boundaries to what is possible in the future. This article provides a...

Weakly Supervised Attention Map Training for Histological Localization of Colonoscopy Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
We consider the problem of training a convolutional neural network for histological localization of colorectal lesions from imperfectly annotated datasets. Given that we have a colonoscopic image dataset for 4-class histology classification and anoth...