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Table 1 List of Shape and Texture Features extracted using GLCM, GLDM, and GLRLM [22]

From: Proficiency evaluation of shape and WPT radiomics based on machine learning for CT lung cancer prognosis

GLCM

Autocorrelation (ACOR), Contrast (CON), Correlation1 (COR1), Correlation2 (COR2), Cluster Prominence (CP), Cluster Shade (CS),Dissimilarity (DS), Energy (ENR), Entropy(ENT), Homogeneity1 (HMG1), Homogeneity2 (HMG2), Maximum Probability (MP), Sum of Squares: Variance(SOS), Sum Average (SA), Sum Variance (SV), Sum Entropy (SE), Difference Variance (DV), Difference Entropy (DE), Information Measure of Correlation1 (IMC1), Information Measure of Correlation2 (IMC2), Inverse Difference Moment(IDM), Inverse Difference Moment Normalized (IDMN)

GLDM

Contrast (CON), Angular Second Moment (ASM), Entropy (ENT), Mean, Inverse Difference Moment (IDM)

GLRLM

Short Run Emphasis (SRE), Long Run Emphasis (LRE), Gray Level Non-uniformity (GLN), Run Length Non-uniformity (RLN), Run Percentage (RP), Low Gray-Level Run Emphasis (LGRE), High Gray-Level Run Emphasis (HGRE), Short Run Low Gray-Level Emphasis (SGLGE), Short Run High Gray-Level Emphasis (SRHGE), Long Run Low Gray-Level Emphasis (LRLGE), Long Run High Gray-Level Emphasis (LRHGE)

Shape Features

Area, Perimeter, MajorAxisLength, MinorAxisLength, Max_Intensity, Mean_Intensity,Min_Intensity