Research Article
Deep-Learning-Based CT Imaging in the Quantitative Evaluation of Chronic Kidney Diseases
Table 1
Average value of the evaluation index of different deep network models on the test set (%).
| | Model | FCN-8S[24] | FCN-16S[24] | FCN-VGG10[19] | U-Net[27] | U-Net (+BN) | UNet++[32] | RDA-UNET |
| | Left kidney | DSC | 88.12 | 87.53 | 95.23 | 92.65 | 95.09 | 94.88 | 96.25 | | Precision | 89.25 | 87.22 | 96.45 | 92.48 | 95.67 | 95.22 | 96.34 | | Recall | 89.88 | 87.43 | 95.55 | 93.66 | 96.45 | 95.88 | 96.88 |
| | Right kidney | DSC | 85.34 | 84.13 | 92.23 | 90.44 | 93.79 | 93.32 | 94.22 | | Precision | 87.83 | 84.23 | 95.88 | 91.67 | 94.67 | 95.11 | 95.34 | | Recall | 87.03 | 88.46 | 91.19 | 92.57 | 94.65 | 94.45 | 94.61 |
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