Grading of Foveal Hypoplasia Using Deep Learning on Retinal Fundus Images
This study strengthened the importance for a pediatric deep learning system to support clinical evaluation, particularly in cases reliant on retinal fundus images.
Authors
- Ying-Feng Chang
- Kuan‐Jen Chen (ORCID: https://orcid.org/0000-0002-4994-8391)
- Nan‐Kai Wang (ORCID: https://orcid.org/0000-0002-6277-9879)
- Jenhui Chen (ORCID: https://orcid.org/0000-0002-8372-9221)
- Tsung‐Ying Tsai (ORCID: https://orcid.org/0000-0001-9926-5727)
- Eugene Yu‐Chuan Kang (ORCID: https://orcid.org/0000-0001-6814-6530)
- Chi‐Chun Lai (ORCID: https://orcid.org/0000-0001-9547-7212)
- Sin-You Chen
- Laura Liu (ORCID: https://orcid.org/0000-0002-3171-3172)
- Yih‐Shiou Hwang (ORCID: https://orcid.org/0000-0003-2744-3234)
- Chao‐Sung Lai (ORCID: https://orcid.org/0000-0002-2069-7533)
- Wei-Chi Wu
Institutions
- Ming Chi University of Technology (TW)
- Chang Gung University (TW)
- Chang Gung Memorial Hospital (TW)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2025-05-22
- DOI
- https://doi.org/10.1167/tvst.14.5.18
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Council
- Chang Gung Medical Foundation
- Chang Gung Memorial Hospital, Linkou
- Center for Big Data Analytics and Statistics, Chang Gung Memorial Hospital
- Center for Big Data Analytics, University of Texas at Austin