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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.