Unsupervised retinal image registration based on D-STUNet and progressive keypoint screening strategy
The proposed network is able to effectively capture local features such as complex vascular structures in retinal images, providing a new method to improve the registration accuracy of retinal images.
Authors
- Xiangyu Deng (ORCID: https://orcid.org/0000-0002-7251-2529)
- Jiayi Kang
Institutions
- Northwest Normal University (CN)
Publication Details
- Journal
- Biomedical Physics & Engineering Express
- Published
- 2025-06-30
- DOI
- https://doi.org/10.1088/2057-1976/ade9c6
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China