Brain Tumor Segmentation on BRATS 2018
| Rank | Model | Dice Score | ET | IoU | MSD | TC | VS | WT | Paper | Code | Year |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | NVDLMED | 0.87049 | – | – | – | – | – | – | 3D MRI brain tumor segmentation using autoencoder regularization | black0017/MedicalZooPytorch · IAmSuyogJadhav/3d-mri-brain-tumor-segmentation-using-autoencoder-regularization · athon2/BraTS2018_NvNet · +4 | 2018 |
| 2 | MS-Dual-Guided | 0.8037 | – | – | 0.9 | – | 93.08 | – | Multi-scale self-guided attention for medical image segmentation | sinAshish/Multi-Scale-Attention | 2019 |
| 3 | 3D-DDA | – | 0.8069 | – | – | 0.8677 | – | 0.9135 | 3D-DDA: 3D Dual-Domain Attention for Brain Tumor Segmentation | sowwnn/3DDualDomainAttention | 2023 |
| 4 | Semantic Genesis | – | – | 68.8 | – | – | – | – | Learning Semantics-enriched Representation via Self-discovery, Self-classification, and Self-restoration | JLiangLab/SemanticGenesis · fhaghighi/SemanticGenesis | 2020 |
| 5 | AMGFormer 자동 추출 | – | 0.5 | – | – | – | – | – | AMGFormer: Adaptive Multi-Granular Transformer for Brain Tumor Segmentation with Missing Modalities | 2026 |