Cardiovascular Disease Detection on OCTA-CVD 1.0 (test)
60.68PrecisionVAMPIRE
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| VAMPIRE2025.07 | 60.68 | 65.7 | 62.71 | 80.12 | 82.44 | 64.67 | |
| PolarNetArchitecture Type=OCTA-based detection method2025.07 | 57.58 | 41.42 | 40.77 | 77.88 | 75.69 | 52.91 | |
| RETFoundArchitecture Type=Fine-tuned ophthalmologic foundation model2025.07 | 56.14 | 58.86 | 54.07 | 78.85 | 80.24 | 58.38 | |
| VisionFMArchitecture Type=Fine-tuned ophthalmologic foundation model2025.07 | 56.1 | 63.51 | 55.22 | 77.39 | 80.61 | 60.09 | |
| Eye-ADArchitecture Type=OCTA-based detection method2025.07 | 51.53 | 63.49 | 57.54 | 75.94 | 75.01 | 53.07 | |
| ViTArchitecture Type=CNN backbone2025.07 | 50.58 | 57.83 | 53.74 | 77.52 | 77.78 | 55.13 | |
| Swin V2Architecture Type=CNN backbone2025.07 | 50.1 | 55.92 | 52.65 | 77.82 | 78.79 | 55.82 | |
| ResNetArchitecture Type=CNN backbone2025.07 | 49.28 | 57.5 | 52.25 | 75.76 | 75.81 | 52.95 | |
| VimArchitecture Type=CNN backbone2025.07 | 46.36 | 55.17 | 48.51 | 78.18 | 79.71 | 57.12 | |
| EfficientNetArchitecture Type=CNN backbone2025.07 | 45.81 | 60.57 | 51.88 | 74.85 | 75.82 | 52.07 |