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. 2024 Jan 8;19(5):851–859. doi: 10.1007/s11548-023-03046-2

Table 3.

Quantitative comparisons among the performance of DeepPyramid+ and alternative methods in organ and disease segmentation, with top two results shown in italic and bold, respectively

Modality Endometriosis surgery MRI OCT
Backbone Network IoU (%) Dice (%) IoU (%) Dice (%) IoU (%) Dice (%) Avg. IoU (%)
VGG16 UNet+ 51.02 64.94 72.44 82.30 51.89 64.95 58.45
scSENet 48.95 62.95 72.31 82.23 52.12 65.18 57.79
FEDNet 50.38 64.16 71.03 81.82 48.70 62.31 56.70
CE-Net 44.40 58.48 70.84 81.27 47.33 61.10 54.19
CPFNet 52.82 66.09 73.28 82.80 47.90 61.17 58.00
UNetPP 51.02 64.83 72.49 82.32 51.58 64.60 58.36
DeepPyramid+ 53.22 66.37 76.02 85.36 50.79 63.99 60.01
ResNet34 scSENet 46.20 60.65 72.99 82.66 49.64 63.31 56.28
FEDNet 28.19 37.85 70.24 80.61 45.34 59.79 47.92
CE-Net 11.02 18.94 13.76 17.51 15.68 25.53 13.49
CPFNet 23.07 35.54 59.95 73.26 18.29 28.99 33.77
DeepPyramid+ 54.04 67.63 73.46 83.66 51.22 64.82 59.57
ResNet50 UPerNet 48.93 62.56 72.73 82.68 46.17 60.18 55.94
DeepLabV3+ 43.00 56.66 70.83 80.79 44.64 58.86 52.82
DeepPyramid+ 53.11 67.12 73.93 83.97 50.99 64.63 59.34

The best results are shown in bold and the second-best are shown in results italic