Using advanced imaging techniques to improve diagnosis of optic nerve diseases
Official title: Deep Learning-based retinal optical coherence tomography markers for optic neuropathies
Funded at University of California-Irvine · NIH-10998041 · Data updated 2026-11-12
This study is working on new ways to help doctors diagnose optic nerve diseases that can cause vision loss by using advanced computer technology to analyze eye images, making it easier to spot problems and track how the condition changes over time.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California-Irvine NIH-funded |
| Lab location | 1 site (Irvine, United States) |
| Project start | July 11, 2024 |
| Project end | July 10, 2029 |
| Funding year | 2024 |
| Award (this year) | $44,850 |
| NIH project number | 1F30EY036725-01 |
| Project ID | NIH-10998041 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals experiencing symptoms of optic neuropathies or those at risk for these conditions due to factors like glaucoma or hereditary predispositions.
✕Less likely to help
Patients with optic neuropathies that are already at an advanced stage or those who do not have access to OCT imaging may not benefit from this research.
What this research studies
This research focuses on developing new diagnostic tools for optic neuropathies, which are diseases affecting the optic nerve and can lead to vision loss. By utilizing deep learning algorithms to analyze optical coherence tomography (OCT) images, the project aims to create innovative biomarkers that can enhance the accuracy of diagnosis. The approach involves advanced computational techniques to identify complex patterns in medical images, addressing current limitations in sensitivity and variability of existing diagnostic methods. This non-invasive imaging technique will provide better insights into the condition of the optic nerve and help in monitoring disease progression.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of optic neuropathies, potentially preventing vision loss for many patients.
How similar studies have gone: Previous research has shown promise in using advanced imaging techniques and machine learning for improving diagnostic accuracy in various medical fields, suggesting potential success for this novel approach.
Where this research is happening
-
University of California-Irvine
Irvine, United States Active
Researchers
- Principal investigator: Khosravi, Pooya — University of California-Irvine
- Study coordinator: Khosravi, Pooya
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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.