Medical Image Segmentation on Hecktor 2022
319.8ThrGVeloxSeg
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| VeloxSegType=CNN-Transformer, MP.=1.66, GF.=2.132025.09 | 319.8 | 5.47 | |
| SegFormer-3DType=CNN-Transformer, MP.=4.50, GF.=6.062025.09 | 305.01 | 2.67 | |
| U-KANType=CNN-KAN, MP.=7.06, GF.=27.132025.09 | 159.92 | 0.75 | |
| Slim UNETRType=CNN-Transformer, MP.=1.77, GF.=4.532025.09 | 151.85 | 8.78 | |
| UNETR++Type=CNN-Transformer, MP.=19.97, GF.=68.662025.09 | 138.39 | 0.56 | |
| UNETRType=CNN-Transformer, MP.=95.76, GF.=99.092025.09 | 105.78 | 0.35 | |
| H-DenseFormerType=CNN-Transformer, MP.=3.64, GF.=85.232025.09 | 102.8 | 0.37 | |
| UNetType=CNN, MP.=5.75, GF.=161.842025.09 | 85.6 | 0.19 | |
| NestedformerType=CNN-Transformer, MP.=4.71, GF.=69.482025.09 | 79.05 | 0.35 | |
| U-RWKVType=CNN-RWKV, MP.=1.44, GF.=24.512025.09 | 73.98 | — | |
| VNetType=CNN, MP.=45.60, GF.=381.892025.09 | 49.82 | 0.11 | |
| SuperLightNetType=CNN-Transformer, MP.=2.75, GF.=23.012025.09 | 47.36 | 0.23 | |
| HCMA-UNetType=CNN-Mamba, MP.=2.81, GF.=31.002025.09 | 46.48 | — | |
| A2FSegType=CNN, MP.=41.32, GF.=246.482025.09 | 40.6 | 0.13 | |
| VSmTransType=CNN-Transformer, MP.=3.12, GF.=28.792025.09 | 34.13 | 0.16 | |
| Swin UNETRType=CNN-Transformer, MP.=15.51, GF.=100.662025.09 | 28.58 | 0.1 | |
| MedNeXt-SType=CNN, MP.=5.54, GF.=68.542025.09 | 23.2 | 0.05 |