TedPic provides an AI‑powered platform that automatically segments orbital structures in ophthalmic images and calculates quantitative disease activity scores for Thyroid Eye Disease. The cloud‑based system delivers results through a web dashboard with longitudinal tracking and integrates via HL7/FHIR APIs into existing EHRs, enabling ophthalmologists and endocrinologists to monitor progression and adjust treatment.
Funding
Funding not disclosed
Founders
Product
Problem
Thyroid Eye Disease (Graves Orbitopathy) requires specialized imaging and expert interpretation to assess disease activity and progression, but many clinics lack standardized tools, leading to delayed diagnoses and inconsistent monitoring. The manual evaluation of orbital changes is time‑consuming and subject to inter‑observer variability, which can hinder timely treatment decisions.
Solution
TedPic offers an AI‑driven software platform that automates the analysis of orbital imaging to deliver rapid, quantitative assessments of Thyroid Eye Disease severity and activity. By applying deep‑learning models to standard ophthalmic photographs and imaging modalities, the system generates objective metrics such as tissue volume, muscle enlargement, and disease activity scores. Results are presented in an intuitive dashboard that tracks changes over time, enabling clinicians to detect progression earlier and adjust therapy with greater confidence. The platform is cloud‑hosted, ensuring secure data storage and easy access from any workstation, and it integrates with existing electronic health record (EHR) systems for seamless workflow incorporation.
Target Audience
The primary customers are ophthalmologists, orbital surgeons, and endocrinologists who manage patients with Graves disease, as well as specialty eye clinics and hospital ophthalmology departments seeking standardized, data‑driven monitoring tools.
Features
- Deep‑learning algorithms trained on a curated dataset of TED imaging to automatically segment extraocular muscles and orbital fat
- Quantitative disease activity index that combines volumetric measurements with clinical parameters for standardized scoring
- Longitudinal tracking module that visualizes metric trends across visits and flags clinically significant changes
- Web‑based dashboard with customizable visualizations, exportable reports, and patient‑level summaries
- HL7/FHIR‑compatible API for direct integration with major EHR platforms and ophthalmology practice management systems
- End‑to‑end encryption and HIPAA‑compliant cloud storage to protect patient data
- Mobile‑optimized interface allowing clinicians to upload images and review results on tablets or smartphones