Retinal Image Annotation Services for Ophthalmology AI
Expert annotation of fundus images, OCT scans, and retinal imaging for eye disease AI. Ophthalmologist-supervised, HIPAA-compliant, FDA-ready.
Why Retinal Image Annotation Quality Matters
Ophthalmic AI for diabetic retinopathy screening, glaucoma detection, and AMD assessment requires precise retinal annotations. Missed microaneurysms or incorrectly graded pathology can lead to delayed treatment. AI Taggers delivers ophthalmologist-verified annotation for clinical-grade eye care AI.
Trusted by ophthalmic device companies, teleophthalmology platforms, and global health organizations to build accurate retinal screening AI.
Our Retinal Image Annotation Capabilities
Diabetic Retinopathy Annotation
Precise labeling of microaneurysms, hemorrhages, exudates, and neovascularization for DR screening AI. Grading according to ETDRS and international classification standards.
Glaucoma Detection Labeling
Optic disc cup-to-disc ratio measurement, RNFL defect annotation, and visual field correlation for glaucoma screening and progression monitoring AI.
Age-Related Macular Degeneration Annotation
Drusen classification, geographic atrophy delineation, and choroidal neovascularization labeling for AMD detection and staging AI systems.
Retinal Vessel Segmentation
Arteriovenous differentiation, vessel caliber measurement, and vascular abnormality detection for cardiovascular risk assessment and retinal vessel analysis AI.
OCT Image Annotation
Retinal layer segmentation, fluid detection, drusen quantification, and epiretinal membrane labeling in optical coherence tomography images.
Fundus Photography Labeling
Comprehensive annotation of fundus images including anatomical landmarks, pathological findings, and image quality assessment for screening AI.
Ophthalmology-Grade Quality Standards
Our retinal annotation workflows integrate subspecialty expertise with international grading standards and clinical validation.
Ophthalmologist-Verified Quality
Every retinal annotation reviewed by board-certified ophthalmologists with subspecialty expertise in retina and medical imaging.
HIPAA-Compliant Workflows
Secure annotation environments with encrypted data handling, patient data protection, and comprehensive audit trails.
International Grading Standards
Annotations follow ETDRS, AREDS, and international classification systems for global applicability and regulatory compliance.
Multi-Reader Consensus
Complex pathology verified by multiple annotators with ophthalmologist arbitration for difficult cases.
Scalable Retinal Screening Data
From pilot validation to large-scale screening datasets, we maintain ophthalmologist-level accuracy across all retinal imaging modalities.
Grading accuracy
Standard aligned
Modality support
Industries We Serve
Ophthalmic Device Manufacturers
FDA-ready training datasets for fundus cameras, OCT systems, and AI-enabled diagnostic devices.
Teleophthalmology Platforms
Powering remote diabetic retinopathy screening, triage systems, and automated preliminary assessments.
Diabetes Care Programs
Building integrated retinal screening AI for diabetes management and preventive eye care initiatives.
Pharmaceutical Research
Clinical trial endpoint analysis, treatment response assessment, and drug efficacy imaging studies.
Primary Care Integration
Point-of-care retinal screening AI for primary care settings, optometry practices, and community health centers.
Global Health Organizations
Accessible screening AI for resource-limited settings, mobile health applications, and population health programs.
Why Ophthalmology AI Teams Choose AI Taggers
Retina Specialist Expertise
Annotation teams trained by retina specialists with disease-specific certification programs.
FDA-Ready Quality
Documentation and validation protocols structured for regulatory submission and clinical deployment.
Multi-Modality Support
Native handling of fundus photography, OCT, and fluorescein angiography with format preservation.
Secure PHI Handling
De-identification services, encrypted workflows, and isolated annotation environments for patient data.
Our Retinal Annotation Process
Clinical Requirements Review
We analyze your imaging modality, pathology targets, and clinical use case to develop ophthalmologist-approved annotation guidelines.
Validation Phase
Annotate representative images with ophthalmologist review. Establish grading accuracy benchmarks before production.
Production Annotation
Trained annotators label your retinal dataset with continuous quality monitoring and specialist oversight.
Expert Validation
Retina specialist review with delivery in your preferred format including JSON, XML, or research standards.
Real Results From Ophthalmology AI Teams
"AI Taggers' diabetic retinopathy annotation quality matched our retina specialists' grading. Essential for our FDA clearance submission."
VP of Clinical Affairs
Ophthalmic AI Device Company
"The OCT segmentation accuracy enabled our glaucoma detection AI to achieve clinical-grade performance. Outstanding retinal expertise."
Director of AI Research
Eye Care Technology Startup
Get Started With Expert Retinal Image Annotation
Whether you're building DR screening AI, training glaucoma detection models, or developing OCT analysis tools, AI Taggers delivers the clinical-grade annotation your ophthalmology AI requires.
Questions about retinal image annotation?
What retinal pathologies need labeling?
What imaging modalities are in your dataset?
What grading standards do you require?
Are there regulatory requirements to meet?
Our ophthalmology annotation team responds within 24 hours with a tailored solution for your retinal AI project.