Table 5 The segmentation results (mean ± std) on the external validation dataset GUSI-B. The best results are highlighted in bold.

From: SATU-net: a shadow adaptive tracing U-net for gastric cavity segmentation based on the principle of ultrasound imaging

Metric

Ours

U-net

AAU-Net

R2U-Net

LGANet

FAT-Net

Swin-UNet

Transfuse

Accuracy

98.22 ± 0.22

98.02 ± 0.19

98.06 ± 0.24

96.21 ±0.38

97.93±0.19

97.93±0.21

97.53±0.19

98.02±0.41

Precision

88.10 ± 2.81

86.83±5.57

85.10±6.04

73.36±1.91

86.97±5.87

87.62±4.57

85.07±0.77

87.00±7.14

Recall

90.49±0.70

90.13 ± 5.22

94.30 ±4.51

84.12 ± 8.82

88.68±5.86

87.48±5.63

84.49±1.91

90.32±5.73

IoU

80.60± 1.87

78.78±1.07

80.28±1.53

64.16±4.65

77.67±1.15

77.44±2.30

73.59±1.93

78.91±3.01

Dice

89.25 ± 1.14

88.12±0.67

88.98±0.91

78.07±3.47

87.43±0.73

87.26±1.45

84.77±1.28

88.19±1.89

Specificity

98.91 ± 0.30

98.72±0.63

98.39±0.66

97.27±0.48

98.74±0.68

98.86±0.50

98.69±0.06

98.71±0.79

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