Medical Image Segmentation on Brain Tumor (Efficiency)
4.5Params (M)SegFormer
Evaluation results
| Method | Links | ||
|---|---|---|---|
| SegFormerInput patch dimensions=96 × 96 × 962026.05 | 4.5 | 5.02 | |
| MedNeXtInput patch dimensions=96 × 96 × 962026.05 | 11.65 | 178.05 | |
| FEFormerInput patch dimensions=96 × 96 × 962026.05 | 18.54 | 39.13 | |
| TransBTSInput patch dimensions=96 × 96 × 962026.05 | 31.58 | 110.69 | |
| TransHRNetInput patch dimensions=96 × 96 × 962026.05 | 36.86 | 340.33 | |
| V-NetInput patch dimensions=96 × 96 × 962026.05 | 45.66 | 370.52 | |
| VSmTransInput patch dimensions=96 × 96 × 962026.05 | 50.39 | 358.21 | |
| UX NetInput patch dimensions=96 × 96 × 962026.05 | 53.01 | 632.33 | |
| MixUNETRInput patch dimensions=96 × 96 × 962026.05 | 62.03 | 329.99 | |
| Swin UNETRInput patch dimensions=96 × 96 × 962026.05 | 62.19 | 329.28 | |
| nnU-NetInput patch dimensions=96 × 96 × 962026.05 | 68.38 | 357.13 | |
| Att U-NetInput patch dimensions=96 × 96 × 962026.05 | 69.08 | 360.98 | |
| UNETRInput patch dimensions=96 × 96 × 962026.05 | 92.78 | 82.73 | |
| nnFormerInput patch dimensions=96 × 96 × 962026.05 | 149.33 | 284.28 |