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. 2021 May 13;40(9):2463–2476. doi: 10.1109/TMI.2021.3079709

TABLE II. The Segmentation and Classification Performance of Our Model, Human Expert and Other Models. The Metrics are Presented in the Format of Mean (Standard Deviation). Note That the 3D Lesion Segmentation and Classification Subnets in Our Model Are Denoted as Seg. and Cls., Respectively.

Modality Time (s) DSC (%) Sensitivity (%) Specificity (%) NSD (%) RMSD (mm)
Segmentation Human expert 3D 869.2 60.3 (10.8) 61.2 (7.2) 88.7 (1.2) 60.2 (3.6) 12.8 (4.1)
U-Net++L1 2D 1.0 61.2 (5.7) 66.7 (6.4) 90.9 (0.8) 62.4 (3.6) 13.6 (2.3)
U-Net++L4 2D 8.2 65.3 (6.2) 71.3 (5.8) 92.8 (0.6) 66.8 (3.1) 9.6 (2.6)
DenseVNet 3D 2.8 63.7 (7.4) 69.2 (5.9) 92.1 (0.7) 63.6 (2.7) 7.8 (3.1)
COPLE-Net 2D 10.8 67.2 (6.8) 73.4 (7.2) 93.2 (0.6) 68.3 (1.9) 5.2 (2.2)
FSS-2019-nCov 2D 8.7 67.9(7.6) 74.1 (5.2) 93.8 (0.7) 68.8 (2.1) 5.4 (3.0)
DeepSC-COVID w/o Cls. 3D 1.1 66.2 (7.7) 72.7 (4.9) 92.7 (0.8) 64.3 (2.8) 6.2 (2.5)
DeepSC-COVID 3D 2.2 73.3 (8.5) 80.2 (6.8) 95.6 (0.7) 71.8 (2.6) 2.8 (1.6)
Modality Time (s) Accuracy (%) Sensitivity (%) Specificity (%) F1-score (%) AUC (%)
Classification Human expert 3D 378.7 95.8 (0.4) 96.0 (0.4) 97.9 (0.7) 95.7 (0.3)
ResNet-50 2D 9.2 77.7 (0.7) 79.2 (0.2) 87.7 (0.6) 77.9 (0.8) 92.0 (0.1)
3D ResNet-50 3D 0.6 82.5 (0.2) 82.5 (0.7) 90.6 (0.2) 82.0 (0.5) 94.5 (0.2)
COVNet 2D 5.3 87.2 (0.8) 87.6 (0.3) 93.7 (0.4) 87.5 (0.3) 97.4 (0.1)
DeCoVNet 3D 2.3 89.2 (0.5) 89.0 (0.4) 94.3 (0.2) 88.9 (0.8) 98.3 (0.1)
DeepSC-COVID w/o Seg. 3D 0.7 85.2(0.4) 85.3 (0.2) 91.9 (0.3) 84.9 (0.1) 94.4 (0.2)
DeepSC-COVID 3D 2.2 94.5 (0.3) 94.7 (0.2) 97.3 (0.5) 94.2 (0.6) 98.8 (0.1)