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Table 2 Accuracy, precision, recall, and Intersection over Union (IoU) of the OS segmentations

From: Intra-oral scan segmentation using deep learning

Tooth

Accuracy

Precision

Recall

IoUMask

11

0.997

0.935

0.990

0.926

12

0.998

0.923

0.992

0.916

13

0.998

0.931

0.991

0.923

14

0.997

0.935

0.993

0.929

15

0.998

0.941

0.992

0.933

16

0.997

0.961

0.987

0.948

17

0.996

0.946

0.959

0.909

18

0.998

0.966

0.971

0.939

21

0.997

0.931

0.988

0.921

22

0,997

0.916

0.993

0.910

23

0.997

0.911

0.993

0.905

24

0.997

0.937

0.992

0.929

25

0.997

0.937

0.992

0.929

26

0.997

0.955

0.989

0.945

27

0.995

0.940

0.935

0.881

28

0.997

0.880

0.983

0.867

31

0.996

0.899

0.989

0.890

32

0.997

0.919

0.990

0.909

33

0.997

0.927

0.991

0.919

34

0.997

0.932

0.993

0.926

35

0,997

0.937

0.992

0.931

36

0.994

0.959

0,965

0.926

37

0.990

0.941

0.887

0.839

38

0.998

0.955

0.992

0.948

41

0.997

0.906

0.989

0.896

42

0.997

0.918

0.989

0.908

43

0.996

0.915

0.991

0.907

44

0.997

0.933

0.992

0.926

45

0.997

0.940

0.991

0.932

46

0.994

0.958

0.974

0.933

47

0.989

0.935

0.876

0.824

48

0.990

0.934

0.847

0.792