Medical Image Segmentation on ISLES 22
79.85Dice Score (IS)TACO
Evaluation results
| Method | Links | ||
|---|---|---|---|
| TACOPre-training Method=Medical SSL, Backbone=Swin UNETR2026.05 | 79.85 | 77.47 | |
| BrainMVP (Rui et al., 2025)Pre-training Method=Medical SSL, Backbone=UniFormer2026.05 | 79.69 | 76.36 | |
| VoCo (Wu et al., 2024)Pre-training Method=Medical SSL, Backbone=Swin UNETR2026.05 | 79.65 | 75.49 | |
| M3AE (Liu et al., 2023)Pre-training Method=Medical SSL, Backbone=UNET3D2026.05 | 79.13 | 74.93 | |
| Swin UNETR (Tang et al., 2022)Pre-training Method=Medical SSL, Backbone=Swin UNETR2026.05 | 78.71 | 76.26 | |
| S2DC (Pan et al., 2025)Pre-training Method=Medical SSL, Backbone=Swin UNETR2026.05 | 78.49 | 76.13 | |
| SwinMM (Wang et al., 2023c)Pre-training Method=Medical SSL, Backbone=Swin UNETR2026.05 | 77.95 | 76.1 | |
| UNET3DPre-training Method=From Scratch, Backbone=UNET3D2026.05 | 77.81 | 73.28 | |
| Swin UNETRPre-training Method=From Scratch, Backbone=Swin UNETR2026.05 | 77.33 | 75.56 | |
| UniFormerPre-training Method=From Scratch, Backbone=UniFormer2026.05 | 76.52 | 73.55 | |
| UNETRPre-training Method=From Scratch, Backbone=UNETR2026.05 | 76.51 | 70.91 |