3D Brain Tumor Segmentation on BraTS 2019 (val)
0.8Dice (ET)Myronenko et al.
Evaluation results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| Myronenko et al.2021.03 | 0.8 | 0.894 | 0.834 | — | 3.921 | 5.89 | 6.562 | |
| TransBTSTest Time Augmentation (TTA)=true2021.03 | 0.7893 | 0.9 | 0.8194 | — | 3.736 | 5.644 | 6.049 | |
| Frey et al.2021.03 | 0.787 | 0.896 | 0.8 | — | 6.005 | 8.171 | 8.241 | |
| TransBTSTest Time Augmentation (TTA)=false2021.03 | 0.7836 | 0.8889 | 0.8141 | — | 5.908 | 7.599 | 7.584 | |
| Li et al.2021.03 | 0.771 | 0.886 | 0.813 | — | 6.033 | 6.232 | 7.409 | |
| Attention U-Net2021.03 | 0.7596 | 0.8881 | 0.772 | — | 5.202 | 7.756 | 8.258 | |
| Segtran (i3d)Backbone=I3D, Task=3D segmentation2021.05 | 0.74 | 0.895 | 0.817 | 0.817 | — | — | — | |
| V-Net2021.03 | 0.7389 | 0.8873 | 0.7656 | — | 6.131 | 6.256 | 8.705 | |
| Extension of nnU-Netsampling strategies=two sampling strategies2021.05 | 0.737 | 0.894 | 0.807 | 0.813 | — | — | — | |
| Wang et al.2021.03 | 0.737 | 0.894 | 0.807 | — | 5.994 | 5.677 | 7.357 | |
| KiU-Net2021.03 | 0.7321 | 0.876 | 0.7392 | — | 6.323 | 8.942 | 9.893 | |
| Bag of tricksModel Type=single-model, Context=2nd place solution of BraTS'19 challenge2021.05 | 0.729 | 0.904 | 0.802 | 0.812 | — | — | — | |
| 3D U-Net2021.03 | 0.7086 | 0.8738 | 0.7248 | — | 5.062 | 9.432 | 8.719 |