Table 1.
Progressively improved results from our proposed systems are compared with the backbone U-Net model
| Metrics | U-Net+DC | U-Net+CE | FB-Net | FB+SP | FB+SP+SM | |
|---|---|---|---|---|---|---|
| GBM | J (%) | 68.70 | 70.96 | 75.36 | 77.92 | 80.02 |
| P (%) | 83.76 | 82.90 | 87.04 | 90.32 | 91.75 | |
| R (%) | 83.48 | 83.16 | 84.91 | 85.11 | 86.27 | |
| DC (%) | 83.57 | 83.01 | 85.94 | 87.59 | 88.90 | |
| Acc (%) | 90.83 | 92.14 | 93.58 | 94.43 | 95.03 | |
| PQ (%) | 56.72 | 58.91 | 61.76 | 68.25 | 69.13 | |
| HD (pixels) | 41.07 | 41.12 | 39.47 | 39.02 | 37.21 | |
| TCGA | J (%) | 72.60 | 72.26 | 76.78 | 78.28 | 81.80 |
| P (%) | 86.81 | 83.23 | 86.50 | 87.13 | 91.32 | |
| R (%) | 85.07 | 84.30 | 87.10 | 88.52 | 88.90 | |
| DC (%) | 85.93 | 83.73 | 87.09 | 87.81 | 89.95 | |
| Acc (%) | 92.75 | 93.10 | 93.86 | 94.96 | 95.74 | |
| PQ (%) | 58.38 | 57.96 | 61.86 | 65.73 | 68.57 | |
| HD (pixels) | 49.56 | 49.02 | 48.37 | 46.72 | 44.98 | |
| MoNuSeg | J (%) | 65.02 | 65.64 | 69.81 | 70.11 | 72.59 |
| P (%) | 85.29 | 70.06 | 76.87 | 77.13 | 79.86 | |
| R (%) | 73.64 | 91.40 | 88.57 | 88.72 | 88.85 | |
| DC (%) | 78.71 | 79.21 | 82.17 | 82.38 | 84.03 | |
| Acc (%) | 90.34 | 89.63 | 91.66 | 91.77 | 92.66 | |
| PQ (%) | 47.35 | 50.43 | 55.48 | 54.01 | 60.84 | |
| HD (pixels) | 56.77 | 57.37 | 55.93 | 56.72 | 55.17 | |
Note: The average Jaccard coefficient (J), Precision (P), Recall (R), Dice coefficient (DC), Accuracy (Acc), Panoptic Quality (PQ) and Hausdorff distance (HD) for three independent datasets are presented, respectively. The best performance by each metric and dataset is bolded.