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SOTA
Retinal Vessel Segmentation
Retinal Vessel Segmentation On Stare
Retinal Vessel Segmentation On Stare
Metrics
F1 score
Results
Performance results of various models on this benchmark
Columns
Model Name
F1 score
Paper Title
Repository
Residual U-Net
0.8388
Road Extraction by Deep Residual U-Net
-
R2U-Net
0.8475
Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net) for Medical Image Segmentation
-
U-Net
0.8373
U-Net: Convolutional Networks for Biomedical Image Segmentation
-
FSG-Net
0.8510
Full-scale Representation Guided Network for Retinal Vessel Segmentation
-
RV-GAN
0.8323
RV-GAN: Segmenting Retinal Vascular Structure in Fundus Photographs using a Novel Multi-scale Generative Adversarial Network
-
U-Net ASPP
-
Resolution-Aware Design of Atrous Rates for Semantic Segmentation Networks
-
DUNet
0.8143
DUNet: A deformable network for retinal vessel segmentation
-
VGN
0.8429
Deep Vessel Segmentation By Learning Graphical Connectivity
-
0 of 8 row(s) selected.
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Retinal Vessel Segmentation On Stare | SOTA | HyperAI