Table 2.
Performance comparison between state-of-the-art methods (both non-deep learning and deep learning models) and our proposed system (mean, std). The best performance by each metric and dataset is bolded.
| Metrics | mRLS | MOW | IVW | RACM | U-Net + CE | DLV3+ | cGAN | Mask R-CNN | YOLCAT++ | FB + SP + SM | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| GBM | J (%) | 61.88 (4.88) | 68.00 (2.27) | 69.17 (1.79) | 53.17 (3.05) | 70.96 (1.88) | 75.29 (1.93) | 72.45 (1.35) | 72.89 (1.91) | 67.16 (5.54) | 80.02 (0.97) |
| P (%) | 78.35 (2.00) | 73.77 (1.88) | 76.38 (2.03) | 62.15 (2.11) | 82.90 (2.17) | 86.61 (1.70) | 84.24 (1.37) | 86.53 (0.69) | 90.66 (1.10) | 91.75 (2.17) | |
| R (%) | 74.97 (7.89) | 89.72 (3.28) | 88.12 (3.65) | 78.85 (6.35) | 83.16 (1.91) | 85.27 (3.36) | 83.83 (1.65) | 82.24 (2.32) | 72.14 (6.06) | 86.27 (1.88) | |
| DC (%) | 76.35 (3.75) | 80.93 (1.62) | 81.76 (1.25) | 69.38 (2.63) | 83.01 (1.29) | 85.89 (1.26) | 84.02 (0.91) | 84.31 (1.28) | 80.22 (3.92) | 88.90 (0.60) | |
| Acc (%) | 86.47 (1.37) | 90.15 (1.62) | 90.32 (1.64) | 84.47 (2.46) | 92.14 (1.15) | 93.53 (1.04) | 92.63 (1.13) | 92.65 (1.33) | 91.62(2.35) | 95.03 (0.70) | |
| PQ (%) | 55.63 (1.86) | 53.76 (2.34) | 59.64 (2.66) | 37.36 (4.24) | 58.91 (2.53) | 64.66 (1.89) | 60.57 (2.07) | 66.10 (1.79) | 58.11 (7.33) | 68.09 (1.57) | |
| HD (pixels) | 47.58 (6.16) | 40.48 (7.20) | 39.05 (9.48) | 42.69 (5.31) | 41.12 (7.59) | 39.39 (8.53) | 40.91 (7.26) | 39.53 (15.01) | 37.45 (6.77) | 37.21 (5.96) | |
| TCGA | J (%) | 56.08 (5.99) | 74.31 (4.63) | 72.86 (4.54) | 57.44 (3.69) | 72.26 (6.56) | 76.68 (1.41) | 74.65 (2.21) | 81.84 (3.15) | 61.44 (10.87) | 81.80 (3.62) |
| P (%) | 86.15 (2.16) | 87.66 (2.68) | 89.00 (1.97) | 73.92 (1.53) | 83.23 (5.52) | 87.33 (2.00) | 92.92 (0.97) | 91.50 (1.54) | 97.37 (1.52) | 91.32 (3.73) | |
| R (%) | 61.67 (6.88) | 83.08 (5.52) | 80.07 (4.94) | 72.22 (6.11) | 84.30 (3.91) | 86.31 (1.62) | 81.42 (2.45) | 88.58 (3.32) | 62.22 (11.27) | 88.90 (4.75) | |
| DC (%) | 71.68 (5.00) | 85.18 (3.11) | 84.22 (3.09) | 72.90 (3.01) | 83.73 (4.53) | 85.86 (2.35) | 86.77 (1.41) | 89.98 (1.93) | 77.24 (9.69) | 89.95 (2.21) | |
| Acc (%) | 85.99 (1.96) | 93.56 (2.02) | 92.94 (2.18) | 88.12 (2.16) | 93.10 (2.17) | 94.35 (0.83) | 95.03 (0.58) | 95.81 (1.10) | 80.31 (6.73) | 95.74 (1.13) | |
| PQ (%) | 53.11 (6.07) | 56.37 (1.35) | 60.05 (2.92) | 45.18 (0.94) | 57.96 (2.10) | 64.60 (1.93) | 63.60 (2.01) | 68.09 (2.80) | 56.06 (8.51) | 69.91 (2.16) | |
| HD (pixels) | 54.66 (16.72) | 48.54 (4.12) | 46.11 (8.38) | 45.08 (8.26) | 49.02 (9.10) | 47.88 (8.69) | 48.72 (10.17) | 47.48 (20.14) | 65.87 (21.77) | 44.98 (10.44) | |
| MoNuSeg | J (%) | 53.40 (4.37) | 55.57 (13.41) | 67.77 (5.60) | 44.27 (8.68) | 65.64 (3.44) | 69.38 (3.81) | 67.99 (3.32) | 66.24 (6.32) | 51.24 (4.97) | 72.59 (5.14) |
| P (%) | 87.61 (4.43) | 92.39 (4.81) | 90.80 (3.24) | 75.09 (3.92) | 70.06 (3.95) | 76.08 (4.43) | 73.96 (3.69) | 78.25 (9.29) | 68.92 (6.97) | 79.86 (5.05) | |
| R (%) | 57.83 (5.09) | 58.95 (16.17) | 72.70 (5.15) | 52.35 (12.81) | 91.40 (3.86) | 88.94 (4.38) | 89.57 (4.28) | 81.99 (5.64) | 67.05 (6.46) | 88.85 (3.62) | |
| DC (%) | 69.55 (3.70) | 70.80 (11.14) | 80.70 (4.06) | 61.04 (8.21) | 79.21 (2.54) | 81.86 (2.63) | 80.91 (2.39) | 79.51 (4.72) | 67.62 (4.44) | 84.03 (3.39) | |
| Acc (%) | 83.32 (1.53) | 82.50 (9.44) | 90.55 (1.86) | 78.81 (5.58) | 89.63 (1.05) | 91.46 (1.34) | 90.86 (1.01) | 91.56 (2.70) | 85.28 (0.83) | 92.66 (1.65) | |
| PQ (%) | 49.55 (1.54) | 34.68 (13.82) | 51.00 (8.89) | 30.78 (4.42) | 50.43 (2.60) | 57.30 (2.35) | 53.58 (2.63) | 60.33 (6.98) | 54.17 (8.40) | 60.84 (3.47) | |
| HD (pixels) | 68.86 (11.96) | 57.47 (7.39) | 56.54 (6.61) | 56.31 (8.47) | 57.37 (6.63) | 55.86 (7.52) | 56.38 (7.15) | 55.76 (15.22) | 66.99 (9.92) | 55.17 (7.07) | |