Cargando…
Image Segmentation of Retinal Blood Vessels Based on Dual-Attention Multiscale Feature Fusion
Aiming at the problem of insufficient details of retinal blood vessel segmentation in current research methods, this paper proposes a multiscale feature fusion residual network based on dual attention. Specifically, a feature fusion residual module with adaptive calibration weight features is design...
Autores principales: | Gao, Jixun, Huang, Quanzhen, Gao, Zhendong, Chen, Suxia |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279073/ https://www.ncbi.nlm.nih.gov/pubmed/35844462 http://dx.doi.org/10.1155/2022/8111883 |
Ejemplares similares
-
Multiscale U-Net with Spatial Positional Attention for Retinal Vessel Segmentation
por: Liu, Congjun, et al.
Publicado: (2022) -
RFARN: Retinal vessel segmentation based on reverse fusion attention residual network
por: Liu, Wenhuan, et al.
Publicado: (2021) -
DMFF-Net: A dual encoding multiscale feature fusion network for ovarian tumor segmentation
por: Wang, Min, et al.
Publicado: (2023) -
RAFF-Net: An improved tongue segmentation algorithm based on residual
attention network and multiscale feature fusion
por: Song, Haibei, et al.
Publicado: (2022) -
A lightweight network based on dual-stream feature fusion and dual-domain attention for white blood cells segmentation
por: Luo, Yang, et al.
Publicado: (2023)