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Table 2 Texture features at half resolution

From: Optimizing automated characterization of liver fibrosis histological images by investigating color spaces at different resolutions

TA Method

Greylevel

RGB

HSI

COM

Sum of Squares

G_ Sum of Squares

I _ Inverse Difference Moment

 

Sum Entropy

R_ Sum of Squares

S_ Sum of Squares

 

Sum Variance

G_ Sum Entropy

I _ Correlation

RLM

Vertical greylevel non-uniformity

G_45° greylevel non-uniformity

I _Vertical Long Run Emphasis

 

Horizontal greylevel non-uniformity

G_ Horizontal greylevel non-uniformity

I _ Vertical Fraction

 

45° greylevel non-uniformity

G_135°greylevel non-uniformity

I _ Vertical Run length non-uniformity

WT

E 3

G_E 3

I _E 3

 

E 1

G_E 3

I _E 3

 

E 3

G_E 4

I _E 2

  1. The texture features (parameters with the highest F-Coefficient) that discriminate between the C and F groups on greylevel-, RGB-, and HSI- schemes at half resolution images, using TA methods:COM, RLM, and WT.
  2. R_: Red, G_: Green, and B_: Blue channels. H_: Hue, S_: Saturation, and I _: Intensity. E s Energy calculated from the wavelets using various scales (s).
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Theoretical Biology and Medical Modelling

ISSN: 1742-4682