Retinal Vessel Segmentation On Rose 2
Metrics
Dice Score
Results
Performance results of various models on this benchmark
Model Name | Dice Score | Paper Title | Repository |
|---|---|---|---|
| CE-Net | 70.66 | CE-Net: Context Encoder Network for 2D Medical Image Segmentation | |
| OCTA-Net | 70.77 | ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model | |
| OCTAve: OCTA-Net | 71.18 | OCTAve: 2D en face Optical Coherence Tomography Angiography Vessel Segmentation in Weakly-Supervised Learning with Locality Augmentation | |
| U-Net | 65.64 | U-Net: Convolutional Networks for Biomedical Image Segmentation | |
| ResU-Net | 67.25 | Road Extraction by Deep Residual U-Net |
0 of 5 row(s) selected.