Abdomen Organ Segmentation on Abd-CT (20% test)
95.57Dice (Liver)nnUNet
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| nnUNetTraining Strategy=Supervised (80% Training, 20% Testing)2025.12 | 95.57 | 86.75 | 89.39 | 90.83 | 90.64 | |
| IrisTraining Strategy=Supervised (80% Training, 20% Testing), Evaluation Protocol=1-shot protocol (reproduced)2025.12 | 94.52 | 91.66 | 93 | 93.55 | 93.18 | |
| AtlasSegFMTraining Strategy=No Finetuning Required on Target Dataset2025.12 | 90.06 | 63.27 | 62.5 | 75.79 | 72.91 | |
| MAUPTraining Strategy=No Finetuning Required on Target Dataset2025.12 | 78.25 | 59.41 | 71.8 | 60.38 | 67.46 | |
| VM-BaseTraining Strategy=No Finetuning Required on Target Dataset, Evaluation Protocol=1-shot protocol (reproduced)2025.12 | 77.51 | 48.59 | 48.18 | 60.03 | 58.58 | |
| UniverSegTraining Strategy=No Finetuning Required on Target Dataset, Evaluation Protocol=1-shot protocol (reproduced)2025.12 | 77.36 | 32.45 | 46.28 | 36.61 | 48.17 | |
| SegGPTTraining Strategy=No Finetuning Required on Target Dataset, Evaluation Protocol=1-shot protocol (reproduced)2025.12 | 74.64 | 3.61 | 11.7 | 1.03 | 22.74 | |
| FAMNetTraining Strategy=No Finetuning Required on Target Dataset2025.12 | 73.57 | 57.79 | 61.89 | 65.78 | 64.75 | |
| SSL-ALPTraining Strategy=No Finetuning Required on Target Dataset2025.12 | 71.38 | 34.48 | 32.32 | 51.67 | 47.46 | |
| DSPNetTraining Strategy=Finetuned with Other Categories on Target Dataset2025.12 | 69.32 | 78.01 | 74.54 | 69.31 | 72.79 | |
| TycheTraining Strategy=No Finetuning Required on Target Dataset, Evaluation Protocol=1-shot protocol (reproduced)2025.12 | 68.78 | 18.16 | 38.53 | 15.59 | 35.26 | |
| SSL-ALPTraining Strategy=Finetuned with Other Categories on Target Dataset2025.12 | 67.29 | 76.35 | 72.62 | 70.11 | 71.59 | |
| CAT-NetTraining Strategy=Finetuned with Other Categories on Target Dataset2025.12 | 66.24 | 69.09 | 47.83 | 66.98 | 62.54 | |
| RPTTraining Strategy=No Finetuning Required on Target Dataset2025.12 | 65.87 | 40.07 | 35.97 | 51.22 | 48.28 | |
| GMRDTraining Strategy=Finetuned with Other Categories on Target Dataset2025.12 | 63.06 | 79.92 | 62.27 | 56.48 | 65.43 | |
| IFATraining Strategy=No Finetuning Required on Target Dataset2025.12 | 46.92 | 25.13 | 26.56 | 24.85 | 30.79 |