Medical Image Segmentation on Medical Segmentation Decathlon (MSD) (test)
82.14Mean Dice ScoreSwinUNETR
Evaluation results
| Method | Links | ||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SwinUNETR2021.11 | 82.14 | — | — | — | — | — | — | — | — | — | — | — | 94.66 | — | |
| DINTS2021.11 | 81.76 | — | — | — | — | — | — | — | — | — | — | — | 94.03 | — | |
| nnUNet2021.11 | 81.74 | — | — | — | — | — | — | — | — | — | — | — | 93.91 | — | |
| TransVW2021.11 | 81.32 | — | — | — | — | — | — | — | — | — | — | — | 93.72 | — | |
| Models Genesis2021.11 | 81.32 | — | — | — | — | — | — | — | — | — | — | — | 93.72 | — | |
| C2FNAS2021.11 | 81.24 | — | — | — | — | — | — | — | — | — | — | — | 93.49 | — | |
| Kim et al2021.11 | 80.96 | — | — | — | — | — | — | — | — | — | — | — | 93.43 | — | |
| Swin UNETRRank=12021.11 | 78.68 | — | — | — | — | — | — | — | — | — | — | — | 89.28 | — | |
| DINTSRank=22021.11 | 77.93 | — | — | — | — | — | — | — | — | — | — | — | 88.68 | — | |
| nnUNetRank=32021.11 | 77.89 | — | — | — | — | — | — | — | — | — | — | — | 88.09 | — | |
| Models Gen.Rank=42021.11 | 76.97 | — | — | — | — | — | — | — | — | — | — | — | 87.19 | — | |
| Trans VWRank=52021.11 | 76.96 | — | — | — | — | — | — | — | — | — | — | — | 87.64 | — | |
| nnUNetarchitecture=ensemble of models2021.07 | 75 | 61 | 93 | 84 | 89 | 83 | 69 | 66 | 66 | 96 | 56 | 0.15 | — | — | |
| C2FNASarchitecture=single fixed model, GFLOPs=150.782021.07 | 75 | 62 | 92 | 84 | 88 | 82 | 70 | 67 | 67 | 96 | 59 | 0.14 | — | — | |
| CDSSL-P3DBackbone=PVT-small2024.06 | 70.5 | 82.5 | 96.2 | 65.5 | — | — | — | — | 67.8 | — | 50.4 | — | — | 60.5 | |
| ROGarchitecture=single, number of parameters=2.6M, GFLOPs=30.552021.07 | 69 | 56 | 91 | 75 | 89 | 79 | 36 | 66 | 62 | 88 | 46 | 0.18 | — | — | |
| CDSSL-P3DBackbone=ResNet-182024.06 | 68.1 | 81.2 | 96.2 | 63 | — | — | — | — | 65 | — | 46.2 | — | — | 57.1 | |
| UniMiSSBackbone=PVT-small2024.06 | 67.7 | 81.1 | 95.4 | 64.1 | — | — | — | — | 64.3 | — | 44.6 | — | — | 56.7 | |
| MPUNetnumber of parameters=62M2021.07 | 66 | 60 | 89 | 75 | 89 | 77 | 59 | 48 | 48 | 95 | 28 | 0.22 | — | — | |
| PCRLv2Backbone=ResNet-182024.06 | 66 | 79.3 | 95.6 | 61.5 | — | — | — | — | 62.3 | — | 43.2 | — | — | 54.2 | |
| DeSDBackbone=ResNet-182024.06 | 64.6 | 76.8 | 93.9 | 61.8 | — | — | — | — | 62.2 | — | 40.2 | — | — | 52.5 | |
| Rand. init.Backbone=PVT-small2024.06 | 64.5 | 77.9 | 93.5 | 63.5 | — | — | — | — | 63.6 | — | 39.3 | — | — | 49.3 | |
| vox2vecBackbone=ResNet-182024.06 | 63.3 | 78.5 | 96.1 | 61.8 | — | — | — | — | 63.8 | — | 32.6 | — | — | 47.2 | |
| DINOBackbone=ResNet-182024.06 | 62.2 | 76 | 92 | 61.3 | — | — | — | — | 60.8 | — | 37.5 | — | — | 45.6 | |
| TransVWBackbone=ResNet-182024.06 | 62.1 | 76.9 | 93.4 | 61.9 | — | — | — | — | 61.1 | — | 32.7 | — | — | 46.5 | |
| SimSiamBackbone=ResNet-182024.06 | 61.8 | 76.6 | 92 | 61.2 | — | — | — | — | 62.3 | — | 32.5 | — | — | 46.2 | |
| Rand. init.Backbone=ResNet-182024.06 | 60.1 | 75.2 | 92.1 | 60.1 | — | — | — | — | 60.3 | — | 30.6 | — | — | 42.2 |