Segmentation on Liver tumour
69.6DSCPASTA
Evaluation results
| Method | Links | ||
|---|---|---|---|
| PASTAsamples=Full-scale data training (n=131)2025.02 | 69.6 | — | |
| Models Genesissamples=Full-scale data training (n=131)2025.02 | 67.3 | — | |
| nnUNetsamples=Full-scale data training (n=131)2025.02 | 66.6 | — | |
| SuPerMsamples=Full-scale data training (n=131)2025.02 | 65.4 | — | |
| Universalsamples=Full-scale data training (n=131)2025.02 | 64 | — | |
| PASTANo. of Few-shot Samples=162025.02 | 62.9 | — | |
| PASTANo. of Few-shot Samples=82025.02 | 61.7 | — | |
| PASTANo. of Few-shot Samples=42025.02 | 59.8 | — | |
| PASTANo. of Few-shot Samples=22025.02 | 47.7 | — | |
| SuPerMNo. of Few-shot Samples=42025.02 | 39.2 | — | |
| SuPerMNo. of Few-shot Samples=82025.02 | 39 | — | |
| SuPerMNo. of Few-shot Samples=162025.02 | 31.6 | — | |
| SuPerMNo. of Few-shot Samples=22025.02 | 31.3 | — | |
| PASTANo. of Few-shot Samples=12025.02 | 24.3 | 0.004 | |
| SuPerMNo. of Few-shot Samples=12025.02 | 19.4 | 0.004 | |
| Models GenesisNo. of Few-shot Samples=42025.02 | 19.3 | — | |
| nnUNetNo. of Few-shot Samples=42025.02 | 17 | — | |
| nnUNetNo. of Few-shot Samples=22025.02 | 16.4 | — | |
| UniversalNo. of Few-shot Samples=42025.02 | 15.2 | — | |
| Models GenesisNo. of Few-shot Samples=22025.02 | 14.5 | — | |
| UniversalNo. of Few-shot Samples=22025.02 | 14.1 | — | |
| Models GenesisNo. of Few-shot Samples=162025.02 | 13.1 | — | |
| Models GenesisNo. of Few-shot Samples=82025.02 | 10.8 | — | |
| Models GenesisNo. of Few-shot Samples=12025.02 | 10.1 | 0.004 | |
| nnUNetNo. of Few-shot Samples=12025.02 | 9.7 | 0.004 | |
| UniversalNo. of Few-shot Samples=12025.02 | 8 | 0.004 | |
| nnUNetNo. of Few-shot Samples=82025.02 | 6.4 | — | |
| UniversalNo. of Few-shot Samples=82025.02 | 6 | — | |
| nnUNetNo. of Few-shot Samples=162025.02 | 1.8 | — | |
| UniversalNo. of Few-shot Samples=162025.02 | 1.2 | — |