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...
Main Authors: | Dan Yang, Guoru Liu, Mengcheng Ren, Bin Xu, Jiao Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-07-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/22/8/811 |
Similar Items
-
Improvement of Retinal Vessel Segmentation Method Based on U-Net
by: Ning Wang, et al.
Published: (2023-01-01) -
An improved U-net based retinal vessel image segmentation method
by: Kan Ren, et al.
Published: (2022-10-01) -
Blood Vessel Segmentation of Retinal Image Based on Dense-U-Net Network
by: Zhenwei Li, et al.
Published: (2021-11-01) -
MSR U-Net: An Improved U-Net Model for Retinal Blood Vessel Segmentation
by: Giri Babu Kande, et al.
Published: (2024-01-01) -
LEA U-Net: a U-Net-based deep learning framework with local feature enhancement and attention for retinal vessel segmentation
by: Jihong Ouyang, et al.
Published: (2023-05-01)