AIMC Topic: Capsule Endoscopy

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Zoom in Lesions for Better Diagnosis: Attention Guided Deformation Network for WCE Image Classification.

IEEE transactions on medical imaging Nov 30, 2020
Wireless capsule endoscopy (WCE) is a novel imaging tool that allows noninvasive visualization of the entire gastrointestinal (GI) tract without causing discomfort to patients. Convolutional neural networks (CNNs), though perform favorably against tr...
Software Attention Capsule Endoscopy Neural Networks, Computer Machine Learning Humans
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Artificial intelligence that determines the clinical significance of capsule endoscopy images can increase the efficiency of reading.

PloS one Oct 29, 2020
Artificial intelligence (AI), which has demonstrated outstanding achievements in image recognition, can be useful for the tedious capsule endoscopy (CE) reading. We aimed to develop a practical AI-based method that can identify various types of lesio...
Time Factors Humans Image Processing, Computer-Assisted Artificial Intelligence Capsule Endoscopy
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Improved classification and localization approach to small bowel capsule endoscopy using convolutional neural network.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society Aug 31, 2020
BACKGROUND: Although great advances in artificial intelligence for interpreting small bowel capsule endoscopy (SBCE) images have been made in recent years, its practical use is still limited. The aim of this study was to develop a more practical conv...
Humans Deep Learning Capsule Endoscopy Intestine, Small Neural Networks, Computer Artificial Intelligence
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Utilizing artificial intelligence in endoscopy: a clinician's guide.

Expert review of gastroenterology & hepatology Jun 17, 2020
INTRODUCTION: Artificial intelligence (AI) that surpasses human ability in image recognition is expected to be applied in the field of gastrointestinal endoscopes. Accordingly, its research and development (R &D) is being actively conducted. With the...
Humans Deep Learning Rectal Diseases Endoscopy, Gastrointestinal Stomach Neoplasms Colorectal Neoplasms Image Interpretation, Computer-Assisted Capsule Endoscopy Pharyngeal Neoplasms Precancerous Conditions Gastrointestinal Neoplasms Esophageal Neoplasms Colonic Polyps Helicobacter Infections Helicobacter pylori
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Automatic detection of various abnormalities in capsule endoscopy videos by a deep learning-based system: a multicenter study.

Gastrointestinal endoscopy May 15, 2020
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...
Humans Neural Networks, Computer Capsule Endoscopy Intestine, Small Deep Learning
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A primer on artificial intelligence and its application to endoscopy.

Gastrointestinal endoscopy May 7, 2020
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...
Workflow Capsule Endoscopy Humans Artificial Intelligence
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Deep learning for wireless capsule endoscopy: a systematic review and meta-analysis.

Gastrointestinal endoscopy Apr 22, 2020
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...
Retrospective Studies Deep Learning Humans Capsule Endoscopy Neural Networks, Computer Artificial Intelligence
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A pilot trial of Convolution Neural Network for automatic retention-monitoring of capsule endoscopes in the stomach and duodenal bulb.

Scientific reports Mar 5, 2020
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...
Young Adult Adult Male Middle Aged Sensitivity and Specificity Female Humans Aged Neural Networks, Computer Aged, 80 and over Capsule Endoscopy Algorithms Image Processing, Computer-Assisted Stomach Adolescent Capsule Endoscopes Foreign Bodies Retrospective Studies Duodenum Monitoring, Intraoperative Automation
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Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network.

Gastrointestinal endoscopy Feb 19, 2020
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...
Humans Neural Networks, Computer Deep Learning Intestine, Small ROC Curve Capsule Endoscopy
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Classification of stomach infections: A paradigm of convolutional neural network along with classical features fusion and selection.

Microscopy research and technique Jan 27, 2020
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...
Humans Infections Neural Networks, Computer Stomach Diseases Image Processing, Computer-Assisted Algorithms Capsule Endoscopy
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