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Table 2 Nine radiomic features selected by the minimum redundancy maximum relevance algorithm

From: Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas

Number Features Description
1 Cluster Tendency_HLL One of the wavelet features derived from Cluster Tendency. Cluster Tendency is a measure of groupings of voxels with similar gray-level values.
2 Entropy_LLL (group 1 derived) One of the wavelet features derived from Entropy. Entropy specifies the uncertainty/randomness in the image values.
3 Long Run Low Gray Level Emphasis_LHL One of the wavelet features derived from Long Run Low Gray Level Emphasis. Long Run Low Gray Level Emphasis measures the joint distribution of long runs and low gray level values.
4 Minimum Minimum describes the minimum signal intensity.
5 Short Run High Gray Level Emphasis_LLH One of the wavelet features derived from Short Run High Gray Level Emphasis. Short Run High Gray Level Emphasis measures the joint distribution of short runs and high gray level values.
6 Short Run Low Gray Level Emphasis_LLL One of the wavelet features derived from Short Run Low Gray Level Emphasis. Short Run Low Gray Level Emphasis measures the joint distribution of short runs and low gray level values.
7 Short Run Low Gray Level Emphasis_LHH One of the wavelet features derived from Short Run Low Gray Level Emphasis. Short Run Low Gray Level Emphasis measures the joint distribution of short runs and low gray level values.
8 Short Run Low Gray Level Emphasis_HLL One of the wavelet features derived from Short Run Low Gray Level Emphasis. Short Run Low Gray Level Emphasis measures the joint distribution of short runs and low gray level values.
9 Short Run Low Gray Level Emphasis_HLH One of the wavelet features derived from Short Run Low Gray Level Emphasis. Short Run Low Gray Level Emphasis measures the joint distribution of short runs and low gray level values.