Hyperspectral Imaging for the Classification and Analysis of Drusen in Age-Related Macular Degeneration
Distinct spatial-spectral signatures for soft drusen, hard drusen, and RPD were identified using hyperspectral imaging. Both SAM and random forest classifiers demonstrated promising results for automated drusenoid deposit detection. These findings support the role of hyperspectral retinal imaging as a noninvasive tool for automated drusen mapping and patient risk stratification in nonexudative AMD.
Authors
- Jean Daniel Arbour
- Lara Santucci
- Shannon R. Campbell
- Ramina Nissan
- Claudia Chevrefils
- Ioanna Ploumi (ORCID: https://orcid.org/0000-0001-8475-3170)
- C. Chen
- XINYI DING
- Raha Razavi (ORCID: https://orcid.org/0009-0002-9624-7421)
- Khaled Nassar (ORCID: https://orcid.org/0000-0003-4974-3828)
- Heiko G. Niessen
- Francesco Romano
- John B Miller
- Anthéa Rojewski
- Anudeep Konda
- Jean-Philippe Sylvestre
- Marc-André Rhéaume
- Patricia Sorya
- Ying Zhu
- Samin Sabokrohiyeh
Institutions
- Massachusetts Eye and Ear Infirmary (US)
- Boehringer Ingelheim (Germany) (DE)
- Harvard University (US)
- Clinique Paro Excellence (CA)
- Shanghai Eye Disease Prevention & Treatment Center (CN)
- Optina Diagnostics (Canada) (CA)
Publication Details
- Journal
- Investigative Ophthalmology & Visual Science
- Published
- 2026-03-05
- DOI
- https://doi.org/10.1167/iovs.67.3.10
- Primary Topic
- Retinal Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00