Cephalometric Landmark Detection on CephAdoAdu Adult + Adolescent (test)
1.05MRE (mm)CeLDA
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| CeLDABackbone=U-Net, Mask Ratio R=0.72024.06 | 1.05 | 89.13 | 93.6 | 96.17 | 98.67 | |
| Wu et al.2024.06 | 1.34 | 87.17 | 91.93 | 95.57 | 97.1 | |
| GU2NetArchitecture=Universal landmark detection2024.06 | 1.69 | 80.33 | 88.13 | 91.47 | 95.57 | |
| SCNArchitecture=Fully convolutional network2024.06 | 1.73 | 82.97 | 90.4 | 93.37 | 96.57 | |
| Cascade RCNNArchitecture=Multi-stage object detection2024.06 | 2.31 | 61.47 | 73.2 | 81.13 | 90.77 |