WSI Classification on Private-Breast
0.66Top-1 Macro Avg F1PathDino-512
Evaluation Results
| Method | Links | |
|---|---|---|
| PathDino-512Pre-training Domain=Histopathology, Architecture=Transformer, Resolution=5122023.11 | 0.66 | |
| iBOT-PathPre-training Domain=Histopathology, Architecture=Transformer2023.11 | 0.61 | |
| PLIPPre-training Domain=Histopathology, Architecture=Transformer2023.11 | 0.58 | |
| PathDino-224Pre-training Domain=Histopathology, Architecture=Transformer, Resolution=2242023.11 | 0.56 | |
| ConvNext-xlargePre-training Domain=Natural, Architecture=CNN-based2023.11 | 0.51 | |
| DinoSSLPathology-8Pre-training Domain=Histopathology, Architecture=Transformer2023.11 | 0.51 | |
| DinoV1-ViT-b16Pre-training Domain=Natural, Architecture=Transformer, Patch Size=162023.11 | 0.49 | |
| Barlow-Twins-ResNet50Pre-training Domain=Histopathology, Architecture=CNN-based2023.11 | 0.49 | |
| MoCoV2-ResNet50Pre-training Domain=Histopathology, Architecture=CNN-based2023.11 | 0.49 | |
| ConvNext-b-224Pre-training Domain=Natural, Architecture=CNN-based, Resolution=2242023.11 | 0.47 | |
| MuDiPath-DenseNet-101Pre-training Domain=Histopathology, Architecture=CNN-based2023.11 | 0.47 | |
| KimiaNetPre-training Domain=Histopathology, Architecture=CNN-based2023.11 | 0.47 | |
| DinoV2-ViT-b14Pre-training Domain=Natural, Architecture=Transformer, Patch Size=142023.11 | 0.46 | |
| ResNet50Pre-training Domain=Natural, Architecture=CNN-based2023.11 | 0.43 | |
| EfficientNet-b5Pre-training Domain=Natural, Architecture=CNN-based2023.11 | 0.41 | |
| DinoV1-ViT-s16Pre-training Domain=Natural, Architecture=Transformer, Patch Size=162023.11 | 0.41 | |
| MuDiPath-ResNet50Pre-training Domain=Histopathology, Architecture=CNN-based2023.11 | 0.41 | |
| CLIP - ViT-B/16Pre-training Domain=Natural, Architecture=Transformer, Patch Size=162023.11 | 0.39 | |
| BiomedCLIPPre-training Domain=Histopathology, Architecture=Transformer2023.11 | 0.39 | |
| DenseNet121Pre-training Domain=Natural, Architecture=CNN-based2023.11 | 0.37 | |
| EfficientNet-b3-288Pre-training Domain=Natural, Architecture=CNN-based, Resolution=2882023.11 | 0.35 | |
| HIPT-ViT-s16Pre-training Domain=Histopathology, Architecture=Transformer, Patch Size=162023.11 | 0.33 | |
| ViT-b16-224Pre-training Domain=Natural, Architecture=Transformer, Patch Size=16, Resolution=2242023.11 | 0.3 |