Table 4 The performance comparison of framework with embedding PAE module and the SOTA in the Public Dataset BS-80K.

From: Automatic detecting multiple bone metastases in breast cancer using deep learning based on low-resolution bone scan images

Model

Value

Map

Backbone

Mean ± Std

50.0 ± 2.6%

Median

49.5%

95% CI

47.9%, 52.1%

Effect sizes

5.914

p value

*\(p<0.0125\)

Cascade R-CNN20

Mean ± Std

61.2 ± 0.7%

Median

61.2%

95% CI

60.6%, 61.7%

Effect sizes

2.645

p value

*\(p<0.0125\)

Faster R-CNN20

Mean ± Std

61.9 ± 0.6%

Median

61.9%

95% CI

61.4%, 62.4%

Effect sizes

1.914

p value

*\(p<0.0125\)

Backbone+DH module

Mean ± Std

62.0 ± 0.6%

Median

62.0%

95% CI

61.5%, 62.5%

Effect sizes

1.23

p value

*\(p<0.0125\)

Our SAAI-BMDetector (with PAE module)

Mean ± Std

63.1 ± 0.7%

Median

63.1%

95% CI

62.6%, 63.6%

  1. *\(p<0.0125\), Bonferroni-adjusted Wilcoxon signed rank test.