RetinalVasNet: a deep learning approach for robust retinal microvasculature detection
The findings suggest that each channel provides unique contributions to the vascular segmentation process, emphasizing the importance of incorporating multiple channels for accurate and comprehensive segmentation.
Authors
- Gancheng Zhu (ORCID: https://orcid.org/0000-0002-4329-4219)
- Weiming Xie (ORCID: https://orcid.org/0000-0002-8714-4140)
- Zhaomin Yao (ORCID: https://orcid.org/0000-0001-6373-8721)
- Zhiguo Wang (ORCID: https://orcid.org/0000-0003-3686-6220)
- Chao Xing (ORCID: https://orcid.org/0000-0002-1838-0502)
- Guoxu Zhang (ORCID: https://orcid.org/0000-0002-8144-8215)
Institutions
- General Hospital of Shenyang Military Region (CN)
- East China Normal University (CN)
- Zhejiang University (CN)
- Northeastern University (CN)
Publication Details
- Journal
- Frontiers in Molecular Biosciences
- Published
- 2025-08-14
- DOI
- https://doi.org/10.3389/fmolb.2025.1562608
- Citations
- 2
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.72