Deep Learning Approaches to Predict Geographic Atrophy Progression Using Three-Dimensional OCT Imaging
Our study provides important insights on the utility of 3D OCT images for GA disease progression predictions.
Authors
- Verena Steffen
- Frédéric Debraine
- Srinivas R. Sadda (ORCID: https://orcid.org/0000-0002-4939-3306)
- Frank Gerhard Holz (ORCID: https://orcid.org/0000-0001-8019-9272)
- Catherine A. Cukras (ORCID: https://orcid.org/0000-0002-1147-854X)
- Neha Anegondi (ORCID: https://orcid.org/0000-0003-2154-945X)
- Christina Rabe
- Richard F. Spaide (ORCID: https://orcid.org/0000-0001-9720-3610)
- Daniela Ferrara (ORCID: https://orcid.org/0000-0002-1380-7562)
- Simon S. Gao (ORCID: https://orcid.org/0000-0002-7020-037X)
- Karthik Ramesh (ORCID: https://orcid.org/0000-0003-2938-7942)
- Adam Pely
- Miao Zhang (ORCID: https://orcid.org/0000-0002-3242-5957)
- Qi Yang (ORCID: https://orcid.org/0000-0002-4483-2007)
- Kenta Yoshida (ORCID: https://orcid.org/0000-0001-9525-1598)
Institutions
- Roche (Switzerland) (CH)
- University of Bonn (DE)
- University of California, Los Angeles (US)
- Vitreous Retina Macula Consultants of New York (US)
- Doheny Eye Institute (US)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-02-06
- DOI
- https://doi.org/10.1167/tvst.14.2.11
- Citations
- 4
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 5.44
Funders
- Amgen
- Alnylam Pharmaceuticals
- Regeneron Pharmaceuticals
- Apellis Pharmaceuticals
- Carl Zeiss Meditec AG
- Astellas Pharma
- Heidelberg Engineering
- Genentech
- Allergan