Segmentation on DRIVE
81.06Dice CoefficientMTFlow
Evaluation results
| Method | Links | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| MTFlow2026.01 | 81.06 | — | — | — | — | — | 84.93 | 77.52 | 79.34 | 90.03 | |
| U-Net++2026.01 | 80.76 | — | — | — | — | — | 86.2 | 75.97 | 79.09 | 89.89 | |
| CAPEBackbone=2D U-Net2025.04 | 80.3 | 95.2 | 94.6 | 90.5 | 80.2 | 76.4 | — | — | — | — | |
| U-Net2026.01 | 80.21 | — | — | — | — | — | 82.47 | 78.06 | 78.38 | 88.88 | |
| InvMALISBackbone=2D U-Net, Loss=Inverse MALIS2025.04 | 79.3 | 94.6 | 94.7 | 89.9 | 77.7 | 74.5 | — | — | — | — | |
| PercBackbone=2D U-Net, Loss=Perceptual loss, Feature Extractor=VGG192025.04 | 77.3 | 96.3 | 93.5 | 90.4 | 76.8 | 72.8 | — | — | — | — | |
| MSEBackbone=2D U-Net, Loss=MSE loss (LMSE)2025.04 | 77.1 | 97.2 | 92.6 | 90.4 | 68.2 | 66.9 | — | — | — | — | |
| clDiceBackbone=2D U-Net, Loss=clDice loss2025.04 | 76.2 | 94.2 | 93.8 | 88.8 | 74.5 | 70.5 | — | — | — | — |