Medical Image Segmentation on MSD
93.2Dice Score3D RepUX-Net
Evaluation results
| Method | Links | |
|---|---|---|
| 3D RepUX-NetNumber of Parameters=65.8M, FLOPs=757.4G2023.03 | 93.2 | |
| 3D UX-NetKernel size=k=72023.03 | 92.6 | |
| nn-UNetNumber of Parameters=31.2M, FLOPs=743.3G2023.03 | 91.7 | |
| RepOptimizerNumber of Parameters=65.8M, FLOPs=757.4G2023.03 | 91.3 | |
| 3D UX-NetKernel size=k=212023.03 | 90.8 | |
| SwinUNETRNumber of Parameters=62.2M, FLOPs=328.4G2023.03 | 90.1 | |
| TransBTSNumber of Parameters=31.6M, FLOPs=110.4G2023.03 | 88.1 | |
| nnFormerNumber of Parameters=149.3M, FLOPs=240.2G2023.03 | 88 | |
| UNETRNumber of Parameters=92.8M, FLOPs=82.6G2023.03 | 85.7 | |
| S1-Omni-Image2026.06 | 85.28 | |
| Task-Specific Models2026.06 | 78.68 | |
| GPT-Image-22026.06 | 37.87 | |
| Nano Banana 22026.06 | 32.63 | |
| GLM-Image2026.06 | 4.42 | |
| Qwen-Image2026.06 | 3.96 |