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Table 3 Classification results according to the different window sizes of 3 × 3, 5 × 5, 7 × 7, 9 × 9, and 11 × 11. The condition of 3 × 3 mask size had the worst results, while the condition of 5 × 5 provided the best results. This result indicates that the mask size can largely influence the classification performance. Statistically significant differences (p < 0.05) compared with ‘3 × 3’, ‘7 × 7’, ‘9 × 9’, and ‘11 × 11’ are indicated by ‘*’, ‘γ’, ‘†’, and ‘ψ’, respectively, as determined from the student’s t-test

From: Automated classification of dense calcium tissues in gray-scale intravascular ultrasound images using a deep belief network

Mask Size

PPV (%)

NPV (%)

Sensitivity (%)

Specificity (%)

Accuracy (%)

AUC

3 × 3

86.7 ± 0.1

82.5 ± 0.1

81.6 ± 0.1

87.3 ± 0.1

84.5 ± 0.1

0.846 ± 0.002

7 × 7

85.4 ± 0.1

91.8 ± 0.1

92.5 ± 0.1

84.1 ± 0.1

88.3 ± 0.1

0.886 ± 0.001

9 × 9

89.1 ± 0.1

84.0 ± 0.1

82.9 ± 0.1

89.8 ± 0.1

86.3 ± 0.1

0.865 ± 0.001

11 × 11

87.1 ± 0.1

87.4 ± 0.1

87.6 ± 0.1

87.0 ± 0.1

87.3 ± 0.1

0.873 ± 0.001

5 × 5

86.0 ± 0.1†

91.2 ± 0.1*†ψ

92.8 ± 0.1*†ψ

85.1 ± 0.1

88.4 ± 0.1*†

0.886 ± 0.001*â€