AI-powered high-resolution eye scans to measure and classify inflammation in uveitis
Official title: Quantification and Classification of Aqueous and Vitreous Inflammation in Uveitis Using Deep Learning Analysis of Ultrahigh-Resolution OCT
Funded at Oregon Health & Science University · NIH-11163446 · Data updated 2026-11-12
This project will use ultrahigh-resolution OCT scans plus deep learning to count and identify inflammatory cells in the eyes of people with uveitis.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Oregon Health & Science University NIH-funded |
| Lab location | 1 site (Portland, United States) |
| Project start | September 1, 2024 |
| Project end | August 31, 2026 |
| Funding year | 2025 |
| Award (this year) | $156,000 |
| NIH project number | 5R21EY036563-02 |
| Project ID | NIH-11163446 on NIH RePORTER |
Who could benefit from this research
✓Could help
People diagnosed with uveitis who can undergo OCT imaging and have active or suspected intraocular inflammation would be the ideal candidates.
✕Less likely to help
People without uveitis or those who cannot receive clear OCT images (for example due to dense corneal or lens opacities) are unlikely to benefit from this project.
What this research studies
If you have uveitis, researchers will take very detailed, noninvasive OCT images of the fluid in the front (aqueous) and back (vitreous) of your eye. They will use artificial intelligence to count inflammatory cells seen in those images and try to classify different cell types. The team will also estimate protein levels by measuring how light scatters in the images. Together these image-based measurements aim to help doctors distinguish types of uveitis and follow disease severity and treatment response over time.
Why it matters
Potential benefit: Could provide a faster, noninvasive way to help diagnose types of uveitis and track how well treatments are working.
How similar studies have gone: OCT and AI have been used separately in eye disease, but combining ultrahigh-resolution OCT with deep learning to count and classify inflammatory cells in the aqueous and vitreous is a relatively new approach with limited prior clinical validation.
Where this research is happening
-
Oregon Health & Science University
Portland, United States Active
Researchers
- Principal investigator: Li, Yan — Oregon Health & Science University
- Study coordinator: Li, Yan
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.