Automated quantification of retinal non-perfusion areas in ultra-widefield SS-OCTA image of patient with retinal vascular diseases by NP-Unet model
The NP-Unet model can efficiently and accurately segment and quantify NPAs with the ISI in the UWF-SS-OCTA image of BRVO, CRVO and DR, offering a non-invasive, valuable tool for clinical evaluation and treatment guidance.
Authors
- Yiling Ou (ORCID: https://orcid.org/0009-0009-7151-5881)
- Yanjie Zhu (ORCID: https://orcid.org/0009-0005-2548-8334)
- Huirui Xie (ORCID: https://orcid.org/0000-0003-2834-9098)
- Yuling Liao (ORCID: https://orcid.org/0009-0006-3092-5487)
- Xiaoyu Xu (ORCID: https://orcid.org/0000-0002-0246-1535)
- Yan Luo (ORCID: https://orcid.org/0000-0002-5262-4363)
- Mengying Tao (ORCID: https://orcid.org/0000-0002-6036-7133)
- Dongmei Ou (ORCID: https://orcid.org/0009-0001-7853-9984)
- Yukang Jiang (ORCID: https://orcid.org/0000-0001-8274-4676)
- Huiting Li (ORCID: https://orcid.org/0000-0002-4215-8717)
- Jianying Pan (ORCID: https://orcid.org/0000-0003-3584-1822)
- Ting Lan (ORCID: https://orcid.org/0009-0005-4674-9337)
- J J Huang (ORCID: https://orcid.org/0009-0005-5208-0772)
- Xiaoyi Wu (ORCID: https://orcid.org/0009-0009-5021-1141)
- Ting Tian (ORCID: https://orcid.org/0000-0002-7148-5629)
Institutions
- Sun Yat-sen University (CN)
- State Key Laboratory of Ophthalmology
Publication Details
- Journal
- BMJ Open Ophthalmology
- Published
- 2025-11-01
- DOI
- https://doi.org/10.1136/bmjophth-2025-002163
- Primary Topic
- Retinal Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Guangdong Province