RetOCTNet: Deep Learning–Based Segmentation of OCT Images Following Retinal Ganglion Cell Injury
This tool automates RNFL and retinal thickness measurement for rat OCT scans following RGC injury, reducing analysis time and increasing the consistency between studies.
Authors
- Machelle T. Pardue (ORCID: https://orcid.org/0000-0001-8738-6839)
- Andrew Feola (ORCID: https://orcid.org/0000-0002-7914-989X)
- Gabriela Sánchez-Rodríguez
- Linjiang Lou (ORCID: https://orcid.org/0000-0003-4343-1284)
Institutions
- Georgia Institute of Technology (US)
- Emory University (US)
- Atlanta VA Health Care System (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-02-04
- DOI
- https://doi.org/10.1167/tvst.14.2.4
- Citations
- 4
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- U.S. Department of Veterans Affairs
- Research to Prevent Blindness
- Emory University
- Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona
- National Institutes of Health
- National Eye Institute