Using deep learning to analyze eye images for glaucoma diagnosis

Deep learning to quantify glaucomatous damage on fundus photographs for teleophthalmology

NIH-funded research Wake Forest University Health Sciences · NIH-10792906

This study is testing a new computer program that looks at pictures of the back of your eye to help doctors better understand damage from glaucoma, so patients can get more accurate diagnoses and better care for their eye health.

Quick facts

Grant typeNIH-funded research
Study typeNIH-funded research
Funding institutionWake Forest University Health Sciences NIH-funded
Lab location1 site (Winston-Salem, United States)
Project IDNIH-10792906 on NIH RePORTER

What this research studies

This research focuses on developing a deep learning algorithm that can accurately assess damage to the optic nerve in patients with glaucoma by analyzing fundus photographs. The goal is to enhance the diagnosis of glaucoma and other eye diseases through advanced imaging technology, particularly in a teleophthalmology setting. Patients will benefit from improved diagnostic accuracy, which could lead to better management of their eye health. The research will also involve training and mentorship for the lead investigator to ensure high-quality outcomes.

Who could benefit from this research

Good fit: Ideal candidates for this research are adults over 21 years old who are at risk for or diagnosed with glaucoma.

Not a fit: Patients with no risk factors for glaucoma or those who do not have access to teleophthalmology services may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more accurate and timely diagnoses of glaucoma, potentially preserving vision for many patients.

How similar studies have performed: Other research has shown promising results using deep learning for medical imaging, indicating that this approach has the potential for success.

Where this research is happening

Winston-Salem, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-09 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.