# SCH: Multimodal Retina Image Alignment and Applications

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2022 · $282,085

## Abstract

Progress is the characterization and treatment of retinal disease involves epidemiological and natural history studies which include genetic and environmental risk actor evaluation as well as clinical trials. As treatments advance, it is important to be able to scientifically analyze and interpret a large amount of information that can be procured from different areas and even points on the retina and evaluate retinal structure and function over time in response to therapies. Currently there is a proliferation of technology to provide data and this data comes from many instruments and different companies. It is increasingly difficult for any one person or reading center to evaluate this information. The goal of this proposal is to develop deep-learning based multimodal retinal image processing methods to help the ophthalmologist to quickly detect and diagnose disease.

## Key facts

- **NIH application ID:** 10491208
- **Project number:** 5R01EY033847-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Cheolhong An
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $282,085
- **Award type:** 5
- **Project period:** 2021-09-30 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10491208

## Citation

> US National Institutes of Health, RePORTER application 10491208, SCH: Multimodal Retina Image Alignment and Applications (5R01EY033847-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10491208. Licensed CC0.

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