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. 2022 Apr 14;10(4):729. doi: 10.3390/healthcare10040729

Table 3.

Overal performance of all approaches.

Metrics Area Error Metrics Boundary Error Metrics Time
Methods Ave. TPR Ave. FPR Ave. JI Ave. DSC Ave. AER Ave. HE Ave. MAE Ave. Time (s)
FCN-AlexNet [60] 0.95/-- 0.34/-- 0.74/-- 0.84/-- 0.39/-- 25.1/-- 7.1/-- 5.8
SegNet [61] 0.94/-- 0.16/-- 0.82/-- 0.89/-- 0.22/-- 21.7/-- 4.5/-- 12.1
U-Net [55] 0.92/-- 0.14/-- 0.83/-- 0.90/-- 0.22/-- 26.8/-- 4.9/-- 2.15
CE-Net [66] 0.91/-- 0.13/-- 0.83/-- 0.90/-- 0.22/-- 21.6/-- 4.5/-- 2.0
MultiResUNet [65] 0.93/-- 0.11/-- 0.84/-- 0.91/-- 0.19/-- 18.8/-- 4.1/-- 6.5
RDAU NET [63] 0.91/-- 0.11/-- 0.84/-- 0.91/-- 0.19/-- 19.3/-- 4.1/-- 3.5
SCAN [64] 0.91/-- 0.11/-- 0.83/-- 0.90/-- 0.20/-- 26.9/-- 4.9/-- 4.1
DenseU-Net [67] 0.91/-- 0.16/-- 0.81/-- 0.88/-- 0.25/-- 25.3/-- 5.5/-- 3.5
STAN [21] 0.92/-- 0.09/-- 0.85/-- 0.91/-- 0.18/-- 18.9/-- 3.9/-- 5.8
Xian, et al. [5] 0.81/0.91 0.16/0.10 0.72/0.84 0.83/-- 0.36/-- 49.2/24.4 12.7/5.8 3.5
Shan, et al. [15] 0.81/0.93 1.06/0.13 0.60/-- 0.70/-- 1.25/-- 107.6/18.9 26.6/5.0 3.0
Shao, et al. [6] 0.67/0.81 0.18/0.12 0.61/0.74 0.71/-- 0.51/-- 69.2/50.2 21.3/13.4 3.5
Fuzzy FCN [62] 0.94/-- 0.08/-- 0.88/-- 0.92/-- 0.14/-- 19.8/-- 4.2/-- 6.0
Huang, et al. [19] 0.93/0.93 0.07/0.07 0.87/0.87 0.93/0.93 0.15/0.15 26.0/26.0 4.9/4.9 6.5
Liu, et al. [4]
LR = 1.5
0.82/0.94 0.13/0.08 0.73/0.87 0.84/-- 0.31/-- 44.0/26.3 10.4/-- 27.0
Liu, et al. [22]
LR = 1.9
0.84/0.94 0.07/0.07 0.79/0.88 0.88/-- 0.23/-- 29.0/25.1 7.6/-- 336.0

The values before the slashes are approaches’ performances on the proposed dataset, and after the slashes are their performances reported in the original publications. Notation ‘--’ indicates that the corresponding metric was not reported in the original paper. The best performance in each column is highlighted in bold.