Whole Slide Image Classification on COLON-MSI (test)
80.9AccuracyFR-MIL
Evaluation results
| Method | Links | ||
|---|---|---|---|
| FR-MILBackbone=ResNet18, Loss Formulation=Lbag2022.06 | 80.9 | 88 | |
| FR-MILBackbone=ResNet18, Loss Formulation=Lbag + Lmax + Lfm2022.06 | 80.9 | 90.1 | |
| CLAM-SBBackbone=ResNet182022.06 | 78.6 | 82 | |
| FR-MILBackbone=ResNet18, Loss Formulation=Lbag + Lmax2022.06 | 78 | 83.1 | |
| FR-MILBackbone=ResNet18, Loss Formulation=Lbag + Lfm2022.06 | 77.5 | 84.2 | |
| Max-poolingBackbone=ResNet182022.06 | 76.3 | 85.9 | |
| ABMILBackbone=ResNet182022.06 | 74 | 77.9 | |
| DSMILBackbone=ResNet182022.06 | 73.4 | 81.1 | |
| TransMILBackbone=ResNet182022.06 | 67.6 | 61.7 | |
| MIL-RNNBackbone=ResNet182022.06 | 63 | 63.1 | |
| Mean-poolingBackbone=ResNet182022.06 | 62.4 | 83 |