2D Medical Image Segmentation on EBHI
1.18ASDU2-Net + MAPO
Evaluation results
| Method | Links | ||
|---|---|---|---|
| U2-Net + MAPOBackbone=CNN2025.12 | 1.18 | — | |
| H2Former + MAPOBackbone=Hybrid2025.12 | 1.22 | — | |
| U2-NetBackbone=CNN2025.12 | 1.26 | — | |
| TransAttUNet + MAPOBackbone=Hybrid2025.12 | 1.3 | — | |
| MISSFormer + MAPOBackbone=ViT2025.12 | 1.31 | — | |
| SwinUNet + MAPOBackbone=ViT2025.12 | 1.33 | — | |
| RollingUNet + MAPOBackbone=CNN2025.12 | 1.53 | — | |
| H2FormerBackbone=Hybrid2025.12 | 1.57 | — | |
| TransAttUNetBackbone=Hybrid2025.12 | 1.71 | — | |
| SwinUNetBackbone=ViT2025.12 | 1.84 | — | |
| U-Net + MAPOBackbone=CNN2025.12 | 1.85 | — | |
| MISSFormerBackbone=ViT2025.12 | 1.93 | — | |
| RollingUNetBackbone=CNN2025.12 | 1.99 | — | |
| U-NetBackbone=CNN2025.12 | 2.01 | — | |
| H2FormerBackbone=Hybrid2025.12 | — | 91.25 | |
| H2Former + MAPOBackbone=Hybrid2025.12 | — | 92.44 | |
| MISSFormerBackbone=ViT2025.12 | — | 91.45 | |
| MISSFormer + MAPOBackbone=ViT2025.12 | — | 92.31 | |
| RollingUNetBackbone=CNN2025.12 | — | 86.05 | |
| RollingUNet + MAPOBackbone=CNN2025.12 | — | 90.32 | |
| SwinUNetBackbone=ViT2025.12 | — | 90.75 | |
| SwinUNet + MAPOBackbone=ViT2025.12 | — | 92.25 | |
| TransAttUNetBackbone=Hybrid2025.12 | — | 91.17 | |
| TransAttUNet + MAPOBackbone=Hybrid2025.12 | — | 92.95 | |
| U-NetBackbone=CNN2025.12 | — | 91.84 | |
| U-Net + MAPOBackbone=CNN2025.12 | — | 91.96 | |
| U2-NetBackbone=CNN2025.12 | — | 92.61 | |
| U2-Net + MAPOBackbone=CNN2025.12 | — | 92.64 |