Optic disc segmentation
Deep learning models trained on 180,000+ annotated fundus images identify cup-to-disc ratio, disc haemorrhages, and neuroretinal rim thinning.
Retinotech develops regulated medical software for automated screening of glaucoma suspect features from color fundus photographs — helping ophthalmology networks triage faster across Central Europe.
Optic disc: vertical C/D ratio elevated · RNFL defect pattern detected
Model confidence: 91.4%Unlike general diabetic retinopathy screeners, OpticFlow™ is purpose-built for optic nerve head analysis and glaucoma suspect referral workflows in primary and community eye care.
Deep learning models trained on 180,000+ annotated fundus images identify cup-to-disc ratio, disc haemorrhages, and neuroretinal rim thinning.
Binary triage aligned with EGS guidelines. Integrates with PACS and EMR via DICOM and HL7 FHIR — no proprietary hardware required.
Grad-CAM visualisations highlight regions influencing the model decision, supporting clinical review and audit trails under EU AI Act requirements.
Run on-premise for data residency (Poland, EU) or via our EU-hosted cloud. Typical inference time under 4 seconds per image pair.
Retinotech is developing OpticFlow™ as a software medical device and is actively preparing submissions for EU MDR clearance, US FDA premarket review, and ISO 13485 quality management certification.
"We ran an OpticFlow pilot in our community screening pathway in 2024. Referral accuracy improved and our ophthalmology backlog dropped by roughly 30% during the evaluation period."
"The heatmap overlays make MDT review straightforward. For a Polish-built SAMD still in development, the validation study design and clinical rigour impressed our research committee."
"Pilot setup took two weeks including DICOM routing. Their Kraków team provided on-site validation support — rare for AI software companies."