Cargando…
A Multi-Scale Feature Fusion Method Based on U-Net for Retinal Vessel Segmentation
Computer-aided automatic segmentation of retinal blood vessels plays an important role in the diagnosis of diseases such as diabetes, glaucoma, and macular degeneration. In this paper, we propose a multi-scale feature fusion retinal vessel segmentation model based on U-Net, named MSFFU-Net. The mode...
Autores principales: | Yang, Dan, Liu, Guoru, Ren, Mengcheng, Xu, Bin, Wang, Jiao |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517387/ https://www.ncbi.nlm.nih.gov/pubmed/33286584 http://dx.doi.org/10.3390/e22080811 |
Ejemplares similares
-
An improved U-net based retinal vessel image segmentation method
por: Ren, Kan, et al.
Publicado: (2022) -
SFA-Net: Scale and Feature Aggregate Network for Retinal Vessel Segmentation
por: Ni, Jiajia, et al.
Publicado: (2022) -
MFI-Net: A multi-resolution fusion input network for retinal vessel segmentation
por: Jiang, Yun, et al.
Publicado: (2021) -
DBFU-Net: Double branch fusion U-Net with hard example weighting train strategy to segment retinal vessel
por: Huang, Jianping, et al.
Publicado: (2022) -
Dense U-net Based on Patch-Based Learning for Retinal Vessel Segmentation
por: Wang, Chang, et al.
Publicado: (2019)