AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Capsule Endoscopy

Showing 51 to 60 of 111 articles

Clear Filters

Automatic detection of various abnormalities in capsule endoscopy videos by a deep learning-based system: a multicenter study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: A deep convolutional neural network (CNN) system could be a high-level screening tool for capsule endoscopy (CE) reading but has not been established for targeting various abnormalities. We aimed to develop a CNN-based system and...

A primer on artificial intelligence and its application to endoscopy.

Gastrointestinal endoscopy
Artificial intelligence (AI) has emerged as a powerful and exciting new technology poised to impact many aspects of health care. In endoscopy, AI is now being used to detect and characterize benign and malignant GI lesions and assess malignant lesion...

Deep learning for wireless capsule endoscopy: a systematic review and meta-analysis.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Deep learning is an innovative algorithm based on neural networks. Wireless capsule endoscopy (WCE) is considered the criterion standard for detecting small-bowel diseases. Manual examination of WCE is time-consuming and can bene...

A pilot trial of Convolution Neural Network for automatic retention-monitoring of capsule endoscopes in the stomach and duodenal bulb.

Scientific reports
The retention of a capsule endoscope (CE) in the stomach and the duodenal bulb during the examination is a troublesome problem, which can make the medical staff spend several hours observing whether the CE enters the descending segment of the duodenu...

Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Protruding lesions of the small bowel vary in wireless capsule endoscopy (WCE) images, and their automatic detection may be difficult. We aimed to develop and test a deep learning-based system to automatically detect protruding l...

Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection.

Microscopy research and technique
Automated detection and classification of gastric infections (i.e., ulcer, polyp, esophagitis, and bleeding) through wireless capsule endoscopy (WCE) is still a key challenge. Doctors can identify these endoscopic diseases by using the computer-aided...

Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Detecting blood content in the gastrointestinal tract is one of the crucial applications of capsule endoscopy (CE). The suspected blood indicator (SBI) is a conventional tool used to automatically tag images depicting possible ble...

A systematic evaluation and optimization of automatic detection of ulcers in wireless capsule endoscopy on a large dataset using deep convolutional neural networks.

Physics in medicine and biology
Compared with conventional gastroscopy which is invasive and painful, wireless capsule endoscopy (WCE) can provide noninvasive examination of gastrointestinal (GI) tract. The WCE video can effectively support physicians to reach a diagnostic decision...

Celiac disease diagnosis from videocapsule endoscopy images with residual learning and deep feature extraction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Videocapsule endoscopy (VCE) is a relatively new technique for evaluating the presence of villous atrophy in celiac disease patients. The diagnostic analysis of video frames is currently time-consuming and tedious. Recently,...

Deep learning algorithms for automated detection of Crohn's disease ulcers by video capsule endoscopy.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The aim of our study was to develop and evaluate a deep learning algorithm for the automated detection of small-bowel ulcers in Crohn's disease (CD) on capsule endoscopy (CE) images of individual patients.