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Table 2 Summary of feature groups in proposed Radiomics-Driven Feature Model (RD-FM) [21]

From: MPCaD: a multi-scale radiomics-driven framework for automated prostate cancer localization and detection

Feature group Number of features Description
Morphology 3 Area regularity (1), Perimeter regularity (2)
Asymmetry 4 Region bilateral symmetry (4)
Physiology 26  
Textural (1st-order) 7 Mean, median, standard deviation, minimum, maximum, kurtosis, skewness
   Energy, contrast, correlation, variance, inverse difference moment normalized, sum average,
Textural (2nd-order) 19 Sum variance, entropy, sum entropy, difference entropy, normalized entropy,
   Information measure of correlation, homogeneity, difference variance,
   Autocorrelation, dissimilarity, cluster shade, cluster prominence, maximum probability
Size 1 Size of region
Total 34 All features