Medical Image Segmentation on BRISC
80.59mIoUMedSAM + Box + Pt
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| MedSAM + Box + PtPrompt Type=Box Predictor + point2026.06 | 80.59 | 89.92 | 89.03 | 88.15 | |
| MedSAM + BoxPrompt Type=Box Predictor2026.06 | 80.35 | 91.06 | 87.7 | 87.93 | |
| MedSAM + pointPrompt Type=point2026.06 | 79.78 | 88.6 | 89.59 | 87.45 | |
| SAM2.1 + pointPrompt Type=point2026.06 | 79.72 | 88.51 | 89.34 | 87.33 | |
| SAM2UNetPrompt Type=Automatic2026.06 | 79.07 | 92.57 | 83.71 | 86.33 | |
| MedSAM2 + pointPrompt Type=point2026.06 | 77.27 | 86.17 | 88.86 | 85.64 | |
| BTI-NetYear=2026, Architecture Category=Transformer-based, Evaluation Mode=Multi-task2026.06 | 76.74 | — | — | — | |
| BTI-NetYear=20262026.06 | 76.74 | — | — | — | |
| SAM + pointPrompt Type=point2026.06 | 76.62 | 87.27 | 87.18 | 84.87 | |
| DeepLabV3+Prompt Type=Automatic2026.06 | 75.53 | 86.22 | 84.25 | 83.42 | |
| MISSFormerYear=2023, Architecture Category=Transformer-based, Evaluation Mode=Single-task2026.06 | 74.83 | — | — | — | |
| DenseMTLYear=20232026.06 | 74.61 | — | — | — | |
| MTI-NetYear=20202026.06 | 73.84 | — | — | — | |
| Swin-UNetYear=2022, Architecture Category=Transformer-based, Evaluation Mode=Single-task2026.06 | 73.42 | — | — | — | |
| UNet++Year=2020, Architecture Category=CNN-based, Evaluation Mode=Single-task2026.06 | 71.84 | — | — | — | |
| MTANetYear=20242026.06 | 71.84 | — | — | — | |
| TransUNetYear=2024, Architecture Category=Transformer-based, Evaluation Mode=Single-task2026.06 | 71.28 | — | — | — | |
| MTL-OCAYear=20252026.06 | 71.24 | — | — | — | |
| MTANYear=20192026.06 | 68.84 | — | — | — | |
| Att-U-NetYear=2018, Architecture Category=CNN-based, Evaluation Mode=Single-task2026.06 | 68.12 | — | — | — | |
| UNetPrompt Type=Automatic2026.06 | 67.3 | 76.04 | 81.94 | 75.55 | |
| U-NetYear=2015, Architecture Category=CNN-based, Evaluation Mode=Single-task2026.06 | 65.84 | — | — | — |