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Table 1 Classification results using cross-validated LDA and for Peritumoral White matter (PtWm) classified as Distant White matter (DWm) (False Negative: FN).

From: The impact of image dynamic range on texture classification of brain white matter

 

16-GL

32-GL

64-GL

128-GL

256-GL

 

FN%

FP%

AUC

FN%

FP%

AUC

FN%

FP%

AUC

FN%

FP%

AUC

FN%

FP%

AUC

CCOM-S1

22.00

15.00

0.82

33.00

5.00

0.81

33.00

10.00

0.785

11.00

5.00

0.915

22.00

15.00

0.815

CCOM-S2

55.00

25.00

0.60

25.00

44.00

0.655

33.00

20.00

0.735

33.00

10.00

0.785

22.00

10.00

0.84

CCOM-S3

33.00

20.00

0.735

33.00

10.00

0.785

11.00

15.00

0.87

11.00

10.00

0.895

22.00

10.00

0.84

Mean ± SD

36.67 ± 16.80

20.00 ± 5.00

0.715

30.33 ± 4.62

19.67 ± 21.22

0.75

25.67 ± 12.70

15.00 ± 5.00

0.8

18.33 ± 12.70

8.33 ± 2.89

0.87

22.00 ± 0.00

11.67 ± 2.89

0.83

3DCOM

22.00

10.00

0.84

22.00

20.00

0.79

33.00

10.00

0.785

11.00

10.00

0.895

44.00

5.00

0.755

  1. DWm classified as PtWM (False Positive: FP); using five dynamic ranges (N = 16, 32, 64, 128, and 256). FN and FP are represented as percentage errors. AUC for each ROC curve is also demonstrated.
  2. CCOM: Classical Cooccurrence Matrix calculated on slices: -S1, -S2, and -S3.
  3. 3DCOM: Three Dimensional Cooccurrence Matrix.
  4. Mean ± SD the average and standard deviation of results for CCOM-S1, CCOM-S2, and CCOM-S3.
  5. GL: Greylevels.
  6. LDA: Linear Discriminant Analysis.
  7. AUC : Area Under the Receiver Operating Characteristic (ROC) Curve.