Development of a computer-aided detection system for colonoscopy and a publicly accessible large colonoscopy video database (with video)

2020/07/31 by Masashi Misawa, Shin-ei Kudo, Shin‐ei Kudo +12 · 27 citations
Medicine · Computer Science · #Colorectal Cancer Screening and Detection #AI in cancer detection #COVID-19 diagnosis using AI

paper · doi:10.1016/j.gie.2020.07.060

Citations

• Polyp Miss Rate Determined by Tandem Colonoscopy: A Systematic Review
• Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience
• Real-Time Use of Artificial Intelligence in Identification of Diminutive Polyps During Colonoscopy
• Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study

Cited by

• Colon-X: Advancing Intelligent Colonoscopy toward Clinical Reasoning
• RRTS Dataset: A Benchmark Colonoscopy Dataset from Resource-Limited Settings for Computer-Aided Diagnosis Research
• Computer-Aided Detection False Positives in Colonoscopy. [europepmc]
• Diagnostic Accuracy of Artificial Intelligence and Computer-Aided Diagnosis for the Detection and Characterization of Colorectal Polyps: Systematic Review and Meta-analysis. [europepmc]
• Artificial intelligence for identification and characterization of colonic polyps. [europepmc]
• A New Dawn for the Use of Artificial Intelligence in Gastroenterology, Hepatology and Pancreatology. [europepmc]
• Optical diagnosis of colorectal polyps using convolutional neural networks. [europepmc]
• Artificial intelligence in gastroenterology: A state-of-the-art review. [europepmc]
• Artificial intelligence-assisted detection and classification of colorectal polyps under colonoscopy: a systematic review and meta-analysis. [europepmc]
• Artificial Intelligence in Endoscopy. [europepmc]
• Artificial Intelligence-Aid Colonoscopy Vs. Conventional Colonoscopy for Polyp and Adenoma Detection: A Systematic Review of 7 Discordant Meta-Analyses. [europepmc]
• On evaluation metrics for medical applications of artificial intelligence. [europepmc]
• Performance of Convolutional Neural Networks for Polyp Localization on Public Colonoscopy Image Datasets. [europepmc]
• Artificial Intelligence in Digestive Endoscopy-Where Are We and Where Are We Going? [europepmc]
• Development and evaluation of a deep learning model to improve the usability of polyp detection systems during interventions. [europepmc]
• Current Status and Future Perspectives of Artificial Intelligence in Colonoscopy. [europepmc]
• Multi-Scale Hybrid Network for Polyp Detection in Wireless Capsule Endoscopy and Colonoscopy Images. [europepmc]
• Detection of Colorectal Polyps from Colonoscopy Using Machine Learning: A Survey on Modern Techniques. [europepmc]
• A Real-Time Polyp-Detection System with Clinical Application in Colonoscopy Using Deep Convolutional Neural Networks. [europepmc]
• The Role of Artificial Intelligence in Monitoring Inflammatory Bowel Disease-The Future Is Now. [europepmc]
• Negative Samples for Improving Object Detection-A Case Study in AI-Assisted Colonoscopy for Polyp Detection. [europepmc]
• Automated classification of polyps using deep learning architectures and few-shot learning. [europepmc]
• Public Imaging Datasets of Gastrointestinal Endoscopy for Artificial Intelligence: a Review. [europepmc]
• GAN Inversion for Data Augmentation to Improve Colonoscopy Lesion Classification. [europepmc]
• Accuracy of artificial intelligence-assisted endoscopy in the diagnosis of gastric intestinal metaplasia: A systematic review and meta-analysis. [europepmc]
• REAL-Colon: A dataset for developing real-world AI applications in colonoscopy. [europepmc]
• Artificial intelligence assisted operative anatomy recognition in endoscopic pituitary surgery. [europepmc]