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Ulcer

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Deep learning-based lesion detection and severity grading of small-bowel Crohn's disease ulcers on double-balloon endoscopy images.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Double-balloon endoscopy (DBE) is widely used in diagnosing small-bowel Crohn's disease (CD). However, CD misdiagnosis frequently occurs if inexperienced endoscopists cannot accurately detect the lesions. The CD evaluation may al...

Deep Learning and Minimally Invasive Endoscopy: Automatic Classification of Pleomorphic Gastric Lesions in Capsule Endoscopy.

Clinical and translational gastroenterology
INTRODUCTION: Capsule endoscopy (CE) is a minimally invasive examination for evaluating the gastrointestinal tract. However, its diagnostic yield for detecting gastric lesions is suboptimal. Convolutional neural networks (CNNs) are artificial intelli...

Deep learning in negative small-bowel capsule endoscopy improves small-bowel lesion detection and diagnostic yield.

Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
OBJECTIVES: Although several studies have shown the usefulness of artificial intelligence to identify abnormalities in small-bowel capsule endoscopy (SBCE) images, few studies have proven its actual clinical usefulness. Thus, the aim of this study wa...

Deep-Learning and Device-Assisted Enteroscopy: Automatic Panendoscopic Detection of Ulcers and Erosions.

Medicina (Kaunas, Lithuania)
: Device-assisted enteroscopy (DAE) has a significant role in approaching enteric lesions. Endoscopic observation of ulcers or erosions is frequent and can be associated with many nosological entities, namely Crohn's disease. Although the application...

Effectiveness of Semi-Supervised Active Learning in Automated Wound Image Segmentation.

International journal of molecular sciences
Appropriate wound management shortens the healing times and reduces the management costs, benefiting the patient in physical terms and potentially reducing the healthcare system's economic burden. Among the instrumental measurement methods, the image...

Deep Convolutional Neural Networks Detect no Morphological Differences Between Culture-Positive and Culture-Negative Infectious Keratitis Images.

Translational vision science & technology
PURPOSE: To determine whether convolutional neural networks can detect morphological differences between images of microbiologically positive and negative corneal ulcers.

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...

Emergent robotic versus laparoscopic surgery for perforated gastrojejunal ulcers: a retrospective cohort study of 44 patients.

Surgical endoscopy
BACKGROUND: Perforated gastrojejunal ulcers are a known complication following Roux-en-Y gastric bypass (RYGB) surgery requiring emergent surgical repair. The robotic approach has not been evaluated for emergency general surgery.

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...