Table 6.
Performance comparison for DeepLab-V3 plus(ex_65) + FRCNN Inception-V2 and other models on the LUNA16 dataset.
| Model | Senstivity | FPs/Scan | Accuracy | Specificity |
|---|---|---|---|---|
| CNN [24] | 70.23% | 4.7 | 74.01% | 79.47% |
| DFCNet [24] | 73.14% | 4.2 | 80.12% | 81.95 |
| RUN:Resdiual-U-Net [12] | 90.9% | 2 | – | – |
| D48 [18] | 91.3% | 1.6 | 94.8% | 98.4% |
| 3D CMixNet Faster-RCNN [17] | 90% | 1.1 | – | – |
| DeepNet [41] | 84.8% | 1 | – | – |
| ResNet [41] | 86.7% | 1 | – | – |
| ResNet+HL [41] | 90.5% | 1 | – | – |
| ESB-ALL [18] | 93.3% | 0.7 | 96.3% | 99.3% |
| Ours Deeplab-V3 plus(ex_65) + FRCNN-Inception-V2 | 96.4% | 0.6 | 97% | 99.4% |