Automatic retinal image analysis methods using colour fundus images for screening glaucomatous optic neuropathy
We used two methods to improve the classification performance and found the best model to detect glaucoma on colour fundus retinal images. It can become a cost-effective and relatively more accurate glaucoma screening tool than conventional methods.
Authors
- Chuying Shi (ORCID: https://orcid.org/0000-0002-8010-8585)
- Di Shi (ORCID: https://orcid.org/0000-0002-4894-732X)
- Gechun Wang
- Benny Zee (ORCID: https://orcid.org/0000-0002-7238-845X)
- J. Jack Lee (ORCID: https://orcid.org/0000-0001-5469-9214)
- Fei Yuan (ORCID: https://orcid.org/0009-0009-7390-3992)
Institutions
- Sun Yat-sen University (CN)
- Chinese University of Hong Kong (HK)
- Fudan University (CN)
- Fudan University Shanghai Cancer Center (CN)
- Hong Kong Jockey Club (HK)
- Affiliated Hospital of Hangzhou Normal University (CN)
- Zhongshan Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
Publication Details
- Journal
- BMJ Open Ophthalmology
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1136/bmjophth-2023-001594
- Citations
- 3
- Primary Topic
- Glaucoma and retinal disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.62