Medical Object Detection On Deeplesion
Métriques
Sensitivity
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Sensitivity |
|---|---|
| advancing-3d-medical-image-analysis-with | 88.55 |
| universal-lesion-detection-by-learning-from | 86.6 |
| improving-retinanet-for-ct-lesion-detection | 82.36 |
| mvp-net-multi-view-fpn-with-position-aware | 83.64 |
| an-efficient-anchor-free-universal-lesion | 86.05 |
| conditional-training-with-bounding-map-for | 86.83 |
| mulan-multitask-universal-lesion-analysis | 85.22 |
| dkma-uld-domain-knowledge-augmented-multi-1 | 87.16 |
| revisiting-3d-context-modeling-with | 86.74 |
| 3d-context-enhanced-region-based | 75.55 |