AIMC Topic: Colonic Polyps
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Development and validation of a novel colonoscopy withdrawal time indicator based on YOLOv5.
Journal of gastroenterology and hepatology
May 6, 2024
BACKGROUND AND AIM: The study aims to introduce a novel indicator, effective withdrawal time (WTS), which measures the time spent actively searching for suspicious lesions during colonoscopy and to compare WTS and the conventional withdrawal time (WT...
UViT-Seg: An Efficient ViT and U-Net-Based Framework for Accurate Colorectal Polyp Segmentation in Colonoscopy and WCE Images.
Journal of imaging informatics in medicine
Apr 26, 2024
Colorectal cancer (CRC) stands out as one of the most prevalent global cancers. The accurate localization of colorectal polyps in endoscopy images is pivotal for timely detection and removal, contributing significantly to CRC prevention. The manual a...
Validation of artificial intelligence-based bowel preparation assessment in screening colonoscopy (with video).
Gastrointestinal endoscopy
Apr 16, 2024
BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of missing >5 mm adenomas and should undergo an early repeat colono...
Multi-scale nested UNet with transformer for colorectal polyp segmentation.
Journal of applied clinical medical physics
Mar 29, 2024
BACKGROUND: Polyp detection and localization are essential tasks for colonoscopy. U-shape network based convolutional neural networks have achieved remarkable segmentation performance for biomedical images, but lack of long-range dependencies modelin...
Artificial Intelligence-Assisted Colonoscopy in Real-World Clinical Practice: A Systematic Review and Meta-Analysis.
Clinical and translational gastroenterology
Mar 1, 2024
INTRODUCTION: Artificial intelligence (AI) could minimize the operator-dependent variation in colonoscopy quality. Computer-aided detection (CADe) has improved adenoma detection rate (ADR) and adenomas per colonoscopy (APC) in randomized controlled t...
Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.
Gastroenterology
Feb 7, 2024
BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal polyps during colonoscopies. However, CADx systems have not yet been validated for autonomous perfo...
Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial.
The American journal of gastroenterology
Feb 2, 2024
INTRODUCTION: Both artificial intelligence (AI) and distal attachment devices have been shown to improve adenoma detection rate and reduce miss rate during colonoscopy. We studied the combined effect of Endocuff and AI on enhancing detection rates of...
Impact of study design on adenoma detection in the evaluation of artificial intelligence-aided colonoscopy: a systematic review and meta-analysis.
Gastrointestinal endoscopy
Jan 24, 2024
BACKGROUND AND AIMS: Randomized controlled trials (RCTs) have reported that artificial intelligence (AI) improves endoscopic polyp detection. Different methodologies-namely, parallel and tandem designs-have been used to evaluate the efficacy of AI-as...
Use of a Novel Artificial Intelligence System Leads to the Detection of Significantly Higher Number of Adenomas During Screening and Surveillance Colonoscopy: Results From a Large, Prospective, US Multicenter, Randomized Clinical Trial.
The American journal of gastroenterology
Jan 18, 2024
INTRODUCTION: Adenoma per colonoscopy (APC) has recently been proposed as a quality measure for colonoscopy. We evaluated the impact of a novel artificial intelligence (AI) system, compared with standard high-definition colonoscopy, for APC measureme...
Two-stage deep-learning-based colonoscopy polyp detection incorporating fisheye and reflection correction.
Journal of gastroenterology and hepatology
Jan 15, 2024
BACKGROUND AND AIM: Colonoscopy is a useful method for the diagnosis and management of colorectal diseases. Many computer-aided systems have been developed to assist clinicians in detecting colorectal lesions by analyzing colonoscopy images. However,...
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