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Table 1 Effectiveness of our proposed method on the dice coefficient, precision, for methods including the primary network, two-stage network, and augmentation(Aug) + oversample strategies

From: A deep semantic segmentation correction network for multi-model tiny lesion areas detection

Method

Task

Segmentation

Detection

Classification

Primary network

a

10.23

9.25

–

b

32.92

16.12

–

Primary network + Aug

a

15.83

12.96

–

b

29.56

15.80

–

Primary network + Oversample

a

34.66

24.07

–

b

54.39

58.06

–

Primary network + Aug + Oversample

a

32.48

52.18

-

b

67.50

80.64

–

Two-stage network

b

26.53

28.23

66.97

Two-stage network + Aug

b

30.17

58.40

75.21

Two-stage network + Oversample

b

67.82

76.47

87.45

Proposed method

b

74.21

91.76

92.89

  1. Task a: segmentation by category information (e.g., background, FCI and LACI); Task b: segmentation by lesion area (e.g., background and lesion area)