# Computational Ophthalmology

> **NIH NIH P30** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $161,102

## Abstract

ABSTRACT
Computational Ophthalmology Core
The Computational Ophthalmology Core provides high-performance computing resources and state-of-the-
art custom computer programming to UCSD vision researchers completing cellular, animal, and human
vision research studies. The data analysis requirements of the vision research community are increasing
exponentially as high resolution retinal imaging datasets become the standard, and genomics research
utilizes exome and whole genome sequencing. The powerful CPU and GPU computational condo clusters
managed by the San Diego Supercomputer Center, the immersive 3-D visualization facility, and custom
software tools provided by this core facilitate analysis of these large datasets. The Computational
Ophthalmology core also supports a computer programmer with image analysis and signal processing
expertise to develop image analysis software toolkits, and to support computational analyses of both basic
science and clinical vision research projects. In addition, essential IT services such as automated off-site
backup, fileservers for secure file-sharing and institutional software licenses (MATLAB, FilemakerPro,
Github, FreezerPro) are provided by the Computational Ophthalmology Core to the UCSD vision research
community.

## Key facts

- **NIH application ID:** 10222684
- **Project number:** 5P30EY022589-09
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** LINDA M ZANGWILL
- **Activity code:** P30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $161,102
- **Award type:** 5
- **Project period:** 2012-07-01 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10222684

## Citation

> US National Institutes of Health, RePORTER application 10222684, Computational Ophthalmology (5P30EY022589-09). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10222684. Licensed CC0.

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