Estimation of foveal avascular zone area from a B-scan OCT image using machine learning algorithms
This study successfully developed machine learning models capable of predicting FAZ area from OCT B-scan images. These findings demonstrate the potential for using OCT images to predict OCTA data, particularly in populations where OCTA imaging is challenging, such as children and the elderly. Future studies could explore the developmental mechanisms of the FAZ and macula, providing new insights into retinal health across different age groups.
Authors
- Ichiro Maruko (ORCID: https://orcid.org/0000-0001-5647-6372)
- Taiji Hasegawa (ORCID: https://orcid.org/0000-0002-9159-3299)
- Taku Toyama (ORCID: https://orcid.org/0009-0001-0388-0635)
- Tomohiro Iida
- Han Zhou (ORCID: https://orcid.org/0000-0002-2916-9323)
- Miki Ikeda
- Makoto Aihara (ORCID: https://orcid.org/0000-0001-6810-0583)
- Takashi Ueta (ORCID: https://orcid.org/0000-0001-5995-7438)
Institutions
- Tokyo Women's Medical University (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- PLoS ONE
- Published
- 2024-12-16
- DOI
- https://doi.org/10.1371/journal.pone.0315825
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Japan Society for the Promotion of Science