Deep learning based retinal hard exudates quantification of optical coherence tomography
The proposed DL model enables accurate segmentation of retinal HE, offering volumetric data with both horizontal and vertical structural information, which enhances visualization and quantification compared to traditional 2D imaging.
Authors
- Chang Ki Yoon (ORCID: https://orcid.org/0000-0003-4637-8044)
- Hyun Woong Kim (ORCID: https://orcid.org/0000-0003-2595-601X)
- Hyung Woo Lee
- Jung Lim Kim
Institutions
- Seoul National University (KR)
- Konkuk University Medical Center (KR)
- Inje University Busan Paik Hospital (KR)
- Nune Eye Hospital (KR)
Publication Details
- Journal
- International Journal of Retina and Vitreous
- Published
- 2025-10-17
- DOI
- https://doi.org/10.1186/s40942-025-00715-z
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.36
Funders
- Inje University