Medical Image Segmentation on Liver Segmentation dataset (test)
95Dice Coefficient3D-UNet w/ MC dropout
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| 3D-UNet w/ MC dropoutLabeled scans=100, Unlabeled scans=02022.06 | 95 | 89.9 | 6.04 | 1.53 | |
| GBDLLabeled scans=5, Unlabeled scans=952022.06 | 93.5 | 88.4 | 7.89 | 2.42 | |
| Double-UALabeled scans=5, Unlabeled scans=95, base_architecture=3D-UNet with MC dropout2022.06 | 92.7 | 87.8 | 12.11 | 4.19 | |
| CoraNetLabeled scans=5, Unlabeled scans=95, base_architecture=3D-UNet with MC dropout2022.06 | 92.3 | 87.7 | 10.84 | 4.28 | |
| Tripled-UALabeled scans=5, Unlabeled scans=95, base_architecture=3D-UNet with MC dropout2022.06 | 92.1 | 86.9 | 11.77 | 3.62 | |
| UA-MTLabeled scans=5, Unlabeled scans=95, base_architecture=3D-UNet with MC dropout2022.06 | 92 | 86.7 | 13.21 | 4.54 |