About this trial
To address the limitations of current AI-based systems that rely on the assumption of a "constant withdrawal speed," this study proposes the integration of the UPD-3 endoscopic positioning system. By using colonoscope withdrawal videos in combination with UPD-3 imaging data as training samples, we aim to develop an AI-powered bowel cleanliness assessment system that incorporates "withdrawal distance" as a weighting factor. This approach is expected to yield a more reliable, objective, and clinically applicable intelligent assessment system that better aligns with real-world clinical practice and endoscopists' operational habits.
Eligibility criteria
Qualifiers
Clear colonoscopy images suitable for BBPS scoring
Complete and clear colonoscopy videos suitable for BBPS scoring
Clear colonoscopy videos with a stable UPD-3 positioning system, without signal drift, disappearance, or other disruptions
Disqualifiers
Blurred colonoscopy images
Colonoscopy images taken from the small intestine or outside the patient's body
Colonoscopy images captured during irrigation or instrument manipulation
Colonoscopy images obtained during chromoendoscopy
Trial design
Treatments tested in this trial
- No Intervention: Observational Cohort