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Capsule Endoscopy

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Gastrointestinal Tract Disease Classification from Wireless Endoscopy Images Using Pretrained Deep Learning Model.

Computational and mathematical methods in medicine
Wireless capsule endoscopy is a noninvasive wireless imaging technology that becomes increasingly popular in recent years. One of the major drawbacks of this technology is that it generates a large number of photos that must be analyzed by medical pe...

Small Bowel Capsule Endoscopy and artificial intelligence: First or second reader?

Best practice & research. Clinical gastroenterology
Several machine learning algorithms have been developed in the past years with the aim to improve SBCE (Small Bowel Capsule Endoscopy) feasibility ensuring at the same time a high diagnostic accuracy. If past algorithms were affected by low performan...

Deep learning and capsule endoscopy: automatic identification and differentiation of small bowel lesions with distinct haemorrhagic potential using a convolutional neural network.

BMJ open gastroenterology
OBJECTIVE: Capsule endoscopy (CE) is pivotal for evaluation of small bowel disease. Obscure gastrointestinal bleeding most often originates from the small bowel. CE frequently identifies a wide range of lesions with different bleeding potentials in t...

A multisystem-compatible deep learning-based algorithm for detection and characterization of angiectasias in small-bowel capsule endoscopy. A proof-of-concept study.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND AND AIMS: Current artificial intelligence (AI)-based solutions for capsule endoscopy (CE) interpretation are proprietary. We aimed to evaluate an AI solution trained on a specific CE system (Pillcam®, Medtronic) for the detection of angiec...

Efficacy of a comprehensive binary classification model using a deep convolutional neural network for wireless capsule endoscopy.

Scientific reports
The manual reading of capsule endoscopy (CE) videos in small bowel disease diagnosis is time-intensive. Algorithms introduced to automate this process are premature for real clinical applications, and multi-diagnosis using these methods has not been ...

Deep Learning and Device-Assisted Enteroscopy: Automatic Detection of Gastrointestinal Angioectasia.

Medicina (Kaunas, Lithuania)
: Device-assisted enteroscopy (DAE) allows deep exploration of the small bowel and combines diagnostic and therapeutic capacities. Suspected mid-gastrointestinal bleeding is the most frequent indication for DAE, and vascular lesions, particularly ang...

Design and implementation of a highly integrated dual hemisphere capsule robot.

Biomedical microdevices
To achieve cancer screening in any appointed position in 3D regions of the gastrointestinal (GI) tract such as esophagus, stomach and colon, a highly integrated dual hemisphere capsule robot (DHCR) with a novel three-layer nested structure is propose...

Automated detection of ulcers and erosions in capsule endoscopy images using a convolutional neural network.

Medical & biological engineering & computing
Capsule endoscopy (CE) is an important tool in the management of patients with known or suspected inflammatory bowel disease. Ulcers and erosions of the enteric mucosa are prevalent findings in these patients. They frequently occur together, and thei...

Identification of Ulcers and Erosions by the Novel Pillcamâ„¢ Crohn's Capsule Using a Convolutional Neural Network: A Multicentre Pilot Study.

Journal of Crohn's & colitis
BACKGROUND AND AIMS: Capsule endoscopy is a central element in the management of patients with suspected or known Crohn's disease. In 2017, PillCamâ„¢ Crohn's Capsule was introduced and demonstrated to have greater accuracy in the evaluation of extensi...

Artificial intelligence and capsule endoscopy: automatic detection of enteric protruding lesions using a convolutional neural network.

Revista espanola de enfermedades digestivas
BACKGROUND AND AIMS: capsule endoscopy (CE) revolutionized the study of the small intestine. Nevertheless, reviewing CE images is time-consuming and prone to error. Artificial intelligence algorithms, particularly convolutional neural networks (CNN),...