DEAF-Net: Detail-Enhanced Attention Feature Fusion Network for Retinal Vessel Segmentation
Author:
Funder
Natural Science Research Project of Tianjin Education Commission
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s10278-024-01207-6.pdf
Reference52 articles.
1. Ma C, Gu Y, Wang Z: TriConvUNeXt: A Pure CNN-Based Lightweight Symmetrical Network for Biomedical Image Segmentation. J Imaging Inform Med: 1–13, 2024
2. Liu J, Zhao D, Shen J, Geng P, Zhang Y, Yang J, Zhang Z: HRD-Net: High resolution segmentation network with adaptive learning ability of retinal vessel features. Comput Biol Med 173: 108295, 2024
3. Kang N, Wang M, Pang C, Lan R, Li B, Guan J, Wang H: Cross-patch feature interactive net with edge refinement for retinal vessel segmentation. Comput Biol Med 174: 108443, 2024
4. Li J, Gao G, Yang L, Liu Y: A retinal vessel segmentation network with multiple-dimension attention and adaptive feature fusion. Comput Biol Med 172: 108315, 2024
5. Tong L, Li T, Zhang Q, Zhang Q, Zhu R, Du W, Hu P: LiViT-Net: A U-Net-like, lightweight Transformer network for retinal vessel segmentation. Comput Struct Biotechnol J 24: 213-224, 2024
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