Medical Image Segmentation on COVID-19 dataset (test)
73.99Dice CoefficientACC-UNet
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| ACC-UNetparams=16.8M, FLOPS=38G2023.08 | 73.99 | — | — | |
| UCTransnetparams=66.4M, FLOPS=38.8G2023.08 | 73.09 | — | — | |
| MultiResUNetparams=7.3M, FLOPS=1.1G2023.08 | 71.33 | — | — | |
| UNetparams=14M, FLOPS=37G2023.08 | 71.21 | — | — | |
| Swin-Unetparams=27.2M, FLOPS=6.2G2023.08 | 68.56 | — | — | |
| SMESwin-Unetparams=169.8M, FLOPS=6.4G2023.08 | 58.4 | — | — | |
| TFCNs2022.07 | 0.7555 | 37.32 | 0.6074 | |
| DDANet2022.07 | 0.7552 | 39.36 | 0.6052 | |
| Segtran2022.07 | 0.7535 | 41.18 | 0.6035 | |
| AttU-net2022.07 | 0.747 | 48.36 | 0.6026 | |
| U-Net2022.07 | 0.7396 | 45.19 | 0.5999 | |
| Res-UNet2022.07 | 0.7353 | 47.54 | 0.5986 | |
| TransUNet2022.07 | 0.7219 | 52.51 | 0.5722 | |
| FC-DenseNet2022.07 | 0.7113 | 54.72 | 0.5552 |