Development and validation of a 3-D deep learning system for diabetic macular oedema classification on optical coherence tomography images
Our DL system achieved high accuracy in multiclassification tasks on DME classification with 3-D OCT images, which can be applied to population-based DME screening.
Authors
- Tsz Kin Ng (ORCID: https://orcid.org/0000-0001-7863-7229)
- Jinqu Huang (ORCID: https://orcid.org/0000-0001-6566-1641)
- Cui Liu (ORCID: https://orcid.org/0000-0002-8399-5765)
- Guihua Zhang (ORCID: https://orcid.org/0000-0002-3298-7220)
- Longting Lin (ORCID: https://orcid.org/0000-0001-7104-9846)
- Peiwen Xie
- Hanfu Wu
- Yongqun Xiong
- Huishan Zhu
- Jie Ji (ORCID: https://orcid.org/0000-0002-8864-2352)
- Mingzhi Zhang (ORCID: https://orcid.org/0000-0001-9032-7274)
- Ji Wang (ORCID: https://orcid.org/0000-0002-0724-7538)
- Yi Zheng (ORCID: https://orcid.org/0000-0002-5140-086X)
- Jianwei Lin (ORCID: https://orcid.org/0000-0001-5712-1581)
Institutions
- Chinese University of Hong Kong (HK)
- Shantou University (CN)
- Shantou University Medical College (CN)
- He Eye Hospital (CN)
Publication Details
- Journal
- BMJ Open
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1136/bmjopen-2025-099167
- Citations
- 3
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- National Natural Science Foundation of China
- Basic and Applied Basic Research Foundation of Guangdong Province