Medical Image Segmentation on SEGRAP
73.1DSCAdaptformer + SAM-COBOT
Evaluation Results
| Method | Links | |
|---|---|---|
| Adaptformer + SAM-COBOTTrainable Parameters (K)=324.0, Backbone=ViT-Base2023.11 | 73.1 | |
| AdaptformerTrainable Parameters (K)=322.7, Backbone=ViT-Base2023.11 | 72.1 | |
| LoRA + SAM-COBOTTrainable Parameters (K)=148.3, Backbone=ViT-Base2023.11 | 70.1 | |
| LoRATrainable Parameters (K)=147.4, Backbone=ViT-Base2023.11 | 68.7 | |
| LightweightTrainable Parameters (K)=0, Backbone=ViT-Base2023.11 | 67.8 | |
| One-Promptsetting=segment everything, mode=zero-shot2023.05 | 62.2 | |
| MedSAMsetting=segment everything, mode=zero-shot2023.05 | 52.3 | |
| MSAsetting=segment everything, mode=zero-shot2023.05 | 47.3 | |
| SAM-Med2Dsetting=segment everything, mode=zero-shot2023.05 | 43.5 | |
| MedSegDiffsetting=segment everything, mode=zero-shot2023.05 | 34.7 | |
| nnUNetsetting=segment everything, mode=zero-shot2023.05 | 26.8 | |
| TransUNetsetting=segment everything, mode=zero-shot2023.05 | 25.5 | |
| Swin-UNetrsetting=segment everything, mode=zero-shot2023.05 | 23.6 | |
| FreezeTrainable Parameters (K)=0, Backbone=ViT-Base2023.11 | 10.5 |