AIMC Topic: Colonic Polyps
Clear Filters Showing 61 to 70 of 170 articles
Computer-aided classification of colorectal segments during colonoscopy: a deep learning approach based on images of a magnetic endoscopic positioning device.
Scandinavian journal of gastroenterology
Dec 2, 2022
OBJECTIVE: Assessment of the anatomical colorectal segment of polyps during colonoscopy is important for treatment and follow-up strategies, but is largely operator dependent. This feasibility study aimed to assess whether, using images of a magnetic...
Comprehensive review of publicly available colonoscopic imaging databases for artificial intelligence research: availability, accessibility, and usability.
Gastrointestinal endoscopy
Sep 7, 2022
BACKGROUND AND AIMS: Publicly available databases containing colonoscopic imaging data are valuable resources for artificial intelligence (AI) research. Currently, little is known regarding the available number and content of these databases. This re...
Automated histological classification for digital pathology images of colonoscopy specimen via deep learning.
Scientific reports
Jul 27, 2022
Colonoscopy is an effective tool to detect colorectal lesions and needs the support of pathological diagnosis. This study aimed to develop and validate deep learning models that automatically classify digital pathology images of colon lesions obtaine...
Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies.
Digestion
Jun 29, 2022
INTRODUCTION: Computer-aided detection (CADe) helps increase colonoscopic polyp detection. However, little is known about other performance metrics like the number and duration of false-positive (FP) activations or how stable the detection of a polyp...
Warning from artificial intelligence against inaccurate polyp size estimation.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Jun 27, 2022
Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions.
United European gastroenterology journal
May 5, 2022
BACKGROUND: The efficiency of artificial intelligence as computer-aided detection (CADe) systems for colorectal polyps has been demonstrated in several randomized trials. However, CADe systems generate many distracting detections, especially during i...
Detection and Classification of Colorectal Polyp Using Deep Learning.
BioMed research international
Apr 15, 2022
Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required to save the life of patients. Cancer grows from polyps which can be either cancerous or noncancerous...
Real-Time Artificial Intelligence-Based Optical Diagnosis of Neoplastic Polyps during Colonoscopy.
NEJM evidence
Apr 13, 2022
BACKGROUND: Artificial intelligence using computer-aided diagnosis (CADx) in real time with images acquired during colonoscopy may help colonoscopists distinguish between neoplastic polyps requiring removal and nonneoplastic polyps not requiring remo...
Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High-Detecting Endoscopist.
Gastroenterology
Apr 12, 2022
Challenges in artificial intelligence for polyp detection.
Digestive endoscopy : official journal of the Japan Gastroenterological Endoscopy Society
Mar 22, 2022
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