ResMU-Net: Residual Multi-kernel U-Net for blood vessel segmentation in retinal fundus images
Author:
Publisher
Elsevier BV
Subject
Health Informatics,Signal Processing,Biomedical Engineering
Reference47 articles.
1. U-net: Convolutional networks for biomedical image segmentation;Ronneberger,2015
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3. Blood vessel segmentation of retinal image based on dense-U-Net network;Li;Micromachines,2021
4. DUNet: A deformable network for retinal vessel segmentation;Jin;Knowl.-Based Syst.,2019
5. A three-stage deep learning model for accurate retinal vessel segmentation;Yan;IEEE J. Biomed. Health Inf.,2019
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1. MPCCN: A Symmetry-Based Multi-Scale Position-Aware Cyclic Convolutional Network for Retinal Vessel Segmentation;Symmetry;2024-09-10
2. Gabor-net with multi-scale hierarchical fusion of features for fundus retinal blood vessel segmentation;Biocybernetics and Biomedical Engineering;2024-04
3. DABT-U-Net: Dual Attentive BConvLSTM U-Net with Transformers and Collaborative Patch-based Approach for Accurate Retinal Vessel Segmentation;International Journal of Engineering;2024
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