AI / Machine Learning / cv-04
Medical Imaging Anomaly Triage
Turns image and video streams into automated inspection, safety, and operational intelligence.
Commercial Scale
$49,500 USD
Risk Reduced
Quality Exposure
Executive Situation
Radiology teams needed a triage assistant that surfaced potentially urgent anomalies from imaging queues without replacing clinical review.
Modular Solutions Response
We trained modality-specific anomaly segmentation models on de-identified DICOM studies and calibrated thresholds for high sensitivity. The queue interface marks heatmaps, study metadata, and uncertainty reasons for radiologist prioritization.
Industry
Healthcare
Category
Computer Vision & Spatial Intelligence
Specialty
Retraining
Evidence Basis
Model + MLOps
parameters
88M 3D U-Net ensemble
latency
1.8s scan series
training
246 GPU hours
loss
L = Dice + focal + Hausdorff
Enterprise Security Gate
Network Access Restricted.
Detailed files, client-specific assumptions, and delivery channels remain controlled.