Liver Segmentation on CARE-LiSeg GED4 2025 (val)
0.973DiceTanglangSled
Evaluation results
| Method | Links | ||
|---|---|---|---|
| TanglangSled2025.12 | 0.973 | 31.01 | |
| TanglangSledTeam=TanglangSled2025.12 | 0.973 | 31.01 | |
| MHIL2025.12 | 0.9705 | 19.55 | |
| MHILTeam=MHIL2025.12 | 0.9705 | 19.55 | |
| SSL-MedSAM2refinement=FSL-nnUNet2025.12 | 0.9704 | 21.28 | |
| Monster2025.12 | 0.9704 | 19.28 | |
| SSL-MedSAM2Team=Ours, Stage=Full pipeline with FSL-nnUNet refinement2025.12 | 0.9704 | 21.28 | |
| MonsterTeam=Monster2025.12 | 0.9704 | 19.28 | |
| InteliLiver2025.12 | 0.97 | 21.34 | |
| InteliLiverTeam=InteliLiver2025.12 | 0.97 | 21.34 | |
| TFFS-MedSAM2refinement=None2025.12 | 0.9592 | 24.71 | |
| TFFS-MedSAM2Team=Ours-TFFS, Stage=Initial pseudo masks prior to refinement2025.12 | 0.9592 | 24.71 |