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Table 2 Summary of quantitative imaging features

From: Evaluation of prognostic models developed using standardised image features from different PET automated segmentation methods

Type/order of statistics Feature Brief definition
Morphological Volume Sum of voxels delineated multiplied by the volume of one voxel
Pre-discretisation SUVmax Maximum uptake of FDG in the MTV
Energy Sum squared SUV values in the MTV
First order Skewness Measures symmetry of intensity histogram
Kurtosis Measures flatness of intensity histogram
Entropy Measures randomness
Second order Dissimilarity Variation of grey level pairs (GLCM). Features were calculated for each unique direction and averaged with a distance setting of 1
Higher order Grey-level non-uniformity Distribution of zone counts for each intensity value (GLSZM)
Zone percentage Fraction of recorded zones compared to maximum possible
Coarseness Measures spatial rate of change in intensity using a distance of 1