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Table 1 Image texture features that are currently defined for all study participants

From: Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status

Analysis groups

Texture features

Texture feature name

References

Gray-level histogram

Standard deviation

STD

[7, 22, 24–26]

Skewness

Skewness

Kurtosis

Kurtosis

Balance

Balance

Gray-level co-occurrence matrix (GLCM)

GLCM Energy

Energy

[24, 25, 27, 29]

GLCM Entropy

Entropy

GLCM Dissimilarity

Dissimilarity

GLCM Contrast

Contrast

GLCM Homogeneity

Homogeneity

GLCM Correlation

Correlation

GLCM Mean

GLCM Mean

GLCM Variance

GLCM Variance

Neighborhood gray-tone difference matrix (NGTDM)

NGTDM Coarseness

NGTDM Coarseness

[24, 28, 29]

NGTDM Contrast

NGTDM Contrast

NGTDM Complexity

Complexity

NGTDM Strength

Strength

NGTDM Busyness

Busyness

Edge frequency analysis

Mean gradient

Mean_Gradient

[29]

Fourier transform (FT) analysis, power spectrum

RMS (root mean square)

FT_RMS

[29]

FMP (first moment of power spectrum)

FT_FMP

SMP (second moment of power spectrum)

FT_SMP

FD (fractal dimension) from power spectrum exponent

FT_FD

Fractal analysis

Intercept of the plot of the standard deviation of the high frequency image as a function of the size the kernel

CD_Yint

[29–31]

Continuous dimension (CD), slope and intercept

CD_Slope

HZ_PROJ

HZ_PROJ

FD of the standard deviation

FD_Sigma

FD of image using thresholds from 5%-85%

FD_TH_5: FD_TH_85

FD of the surface of the breast considering the gray value representing the height

FD_CALDWELL

FD, Minkowski method

FD_Minkowski