Endoscopy AI
Beyond polyp detection — characterization and surgical decision support
Reads colonoscopy video natively. Paris classification, NICE typing, pit pattern analysis, and non-lifting sign detection with auto-generated surgical briefs.
Real-Time Video Analysis
Classification Systems
Core Capabilities
The full endoscopic AI pipeline
Native Video Understanding
Reads colonoscopy video natively at the frame level. No frame sampling or snapshot extraction needed — the scope IS video, and our model treats it as such.
Paris Classification
Automated morphological classification of detected lesions using the Paris endoscopic classification system (0-Ip, 0-Is, 0-IIa, 0-IIb, 0-IIc, 0-III) for standardized reporting.
NICE Typing
Real-time NBI International Colorectal Endoscopic (NICE) classification to predict histology during the procedure, enabling optical diagnosis without biopsy.
Pit Pattern Analysis
Kudo pit pattern analysis using magnification chromoendoscopy features to differentiate neoplastic from non-neoplastic lesions at the mucosal level.
Non-Lifting Sign Detection
Automated detection of the non-lifting sign during saline lift, a critical indicator of submucosal invasion that determines endoscopic resectability.
Surgical Brief Generation
Auto-generated surgical briefs for colectomy referral when lesions exceed endoscopic resectability criteria, including lesion characterization, location, and staging data.
Clinical Pipeline
From detection to surgical decision in one procedure
Polyp Detection
Real-time polyp detection during live colonoscopy with bounding box overlay and confidence scoring, operating at native video frame rate.
Characterization
Paris classification, NICE typing, and pit pattern analysis to characterize each detected lesion morphologically and histologically.
Resectability Assessment
Non-lifting sign detection and submucosal invasion prediction to determine whether endoscopic resection is feasible or surgical referral is required.
Surgical Decision Support
Auto-generated surgical briefs with comprehensive lesion data, recommended approach, and colectomy referral documentation for the surgical team.
Beyond Detection
Where existing solutions stop, PixelMD begins
Current endoscopy AI products focus narrowly on polyp detection. PixelMD extends the clinical value chain from detection through characterization, resectability assessment, and automated surgical referral documentation.
Existing Solutions
PixelMD Endoscopy
PixelMD
Endoscopy AI