Medical Image Segmentation on DRIVE (test)
90.5Dice ScoreAFDAN
Evaluation results
| Method | Links | ||
|---|---|---|---|
| AFDANType=Domain Adaptation2025.12 | 90.5 | 82.6 | |
| DSTC-SSDAType=Domain Adaptation2025.12 | 89 | 80.2 | |
| EHTDIType=Domain Adaptation2025.12 | 88.6 | 79.5 | |
| YOLO11Type=Traditional Model2025.12 | 87.5 | 77.8 | |
| CMFormerType=Traditional Model2025.12 | 86.4 | 76.1 | |
| SimCISType=Traditional Model2025.12 | 85.8 | 75.2 | |
| SAM2Type=Traditional Model2025.12 | 85.4 | 74.5 | |
| S2M-NetLoss=MASL2026.01 | 83.2 | — | |
| PSPNetType=Traditional Model2025.12 | 81.3 | 68.5 | |
| S2M-NetLoss=standard Dice loss2026.01 | 80.16 | — | |
| UMambaLoss=MASL2026.01 | 79.67 | — | |
| DuckNetLoss=MASL2026.01 | 78.89 | — | |
| SwinUNetLoss=MASL2026.01 | 78.34 | — | |
| TransUNetLoss=MASL2026.01 | 77.89 | — | |
| U-Net++Loss=MASL2026.01 | 77.45 | — | |
| UMambaLoss=standard Dice loss2026.01 | 77.45 | — | |
| RAPUNetLoss=MASL2026.01 | 77.12 | — | |
| DuckNetLoss=standard Dice loss2026.01 | 76.92 | — | |
| PraNetLoss=MASL2026.01 | 76.67 | — | |
| SwinUNetLoss=standard Dice loss2026.01 | 76.12 | — | |
| U-NetLoss=MASL2026.01 | 75.92 | — | |
| TransUNetLoss=standard Dice loss2026.01 | 75.67 | — | |
| U-Net++Loss=standard Dice loss2026.01 | 74.78 | — | |
| RAPUNetLoss=standard Dice loss2026.01 | 74.56 | — | |
| PraNetLoss=standard Dice loss2026.01 | 73.92 | — | |
| U-NetLoss=standard Dice loss2026.01 | 73.12 | — |