Aptan.ai provides end-to-end AI data services tailored to ophthalmic care, empowering the development of precise, scalable, and clinically validated ophthalmology AI solutions. Our offerings combine deep clinical domain knowledge, advanced annotation protocols, and strict regulatory and compliance frameworks to deliver data that drives reliable eye-care innovation.
What We Provide
Ophthalmic Imaging Annotation
- High-precision labeling of fundus photography, OCT (Optical Coherence Tomography), OCT-A, fluorescein & indocyanine angiography, slit-lamp images, corneal topography, and ultrasound B-scan
- Segmentation of retinal layers, optic disc, macula, fovea, cornea, lens, and choroidal structures
- Annotation of pathologies including microaneurysms, hemorrhages, exudates, drusen, neovascularization, edema, optic nerve cupping, corneal ulcers, cataract grading, and lesions
Visual Field & Functional Data Labeling
- Labeling of Humphrey & Goldman visual field tests
- Classification of glaucoma progression, scotomas, peripheral vision loss, and neurological defect patterns
- Point-wise defect annotation and severity mapping for model training
Clinical & Ophthalmic EHR Data Structuring
- Labeling of ophthalmology clinical notes, surgery records, prescriptions, and diagnostic reports
- Structuring of ocular measurements such as IOP (Intraocular Pressure), CCT, axial length, keratometry, refractive error, and A-scan biometry
- Annotation of patient history, comorbidities (diabetes, hypertension), ocular risk factors, and treatment timelines
Disease Classification & Progression Modeling
- Curated labeling for diabetic retinopathy, glaucoma, AMD, cataract, retinoblastoma, uveitis, keratoconus, corneal dystrophies, and retinal vascular occlusions
- Longitudinal dataset annotation to enable disease progression tracking and treatment outcome prediction
- Support for AI-based risk stratification, early screening, and prognosis models
Multi-Modal Eye-Care Data Alignment
- Unified integration of fundus, OCT, visual fields, ocular measurements, and clinical text
- Context-aware annotation for building foundation models and multi-modal ophthalmology AI systems
Quality Assurance & Clinical Validation
- Ophthalmologist-led review cycles
- Multi-stage QA checks for accuracy, inter-grader reliability, and clinical consistency
- Secure, compliant, and audit-ready dataset delivery
Key Use Cases
- Automated DR and glaucoma screening
- AI-assisted retinal and corneal disease detection
- Cataract grading and surgical planning support
- Optic nerve and retinal layer analysis using OCT
- Remote eye-care triaging and tele-ophthalmology AI systems
With clinically validated data and scalable annotation pipelines, Aptan.ai accelerates ophthalmology AI innovation that clinicians trust and patients depend on.