Application of texture signatures based on multiparameter-magnetic resonance imaging for predicting microvascular invasion in hepatocellular carcinoma: Retrospective study

Table 2 The 3D texture features of magnetic resonance images

Extraction method	Parameters
Grayscale histogram (9)	Mean, variance, skewness, kurtosis, and percentiles (1%, 10%, 50%, 90%, and 99%)
Grayscale co-occurrence matrix (55)	Angular second order distance, correlation, contrast, entropy, entropy sum, square sum, mean sum, mean difference, inverse distance, entropy difference, standard deviation
Grayscale gradient (5)	Average gradient, gradient variance, gradient skewness, gradient kurtosis, non-zero gradient
Long run matrices (25)	(Horizontal, vertical, 0°, 45°, 135°) Run length non-uniformity, gray value non-uniformity, long run enhancement, short run enhancement, fractional run