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Table 5 Results of variability between ROI sizes

From: Radiomics Feature Extraction from Ultrasound B-Mode Images and Radio-Frequency Signals of the Carotid Arterial Wall: A Feasibility Study

Median

ROI size

Model

Train MSE

Train R2

Test MSE

Test R2

Feature Selected

Feature Name (Feature class)

Feature Type

Med

Var

Lasso

33.86

0.13

30.79

0.17

3

Complexity (NGLDM), Gray-Level Nonuniformity (GLRLM), SdVett_9 (Wavelet transform)

B-mode higher order and Wavelet transform

Med

1

Lasso

33.15

0.15

33.07

0.11

5

Coarseness (NGTDM), Mean Correlation (Avg features), Run length Non-uniformity (GLRLM), meanVett_3 (Wavelet transform), and RF First order: Standard deviation (DEA)

B-mode higher order, Wavelet transform and Rf first order

Med

1.2

Lasso

33.24

0.14

31.87

0.15

6

Entropy (First order), Coarseness (NGTDM), Mean variance (Avg features), SdVett_1 and SdVett_9 (Wavelet transform) and RF first order: Standard deviation (DEA)

B-mode first, higher order, Wavelet transform and Rf first order

Med

1.4

Lasso

36.22

0.07

34.83

0.07

3

Skewness (first order), Coarseness (NGTDM), Gray level non-uniformity (GLRLM)

B-mode first and higher order

Med

1.6

Lasso

–

–

–

–

0

–

–

  1. Dependent Variable: Chronological age. The Mean square Error (MSE) is represented in years
  2. DEA Direct Energy attenuation map, GLDM Grey Level Distance Matrix, GLRLM Grey Level Run Length Matrix, NGLDM Neighboring Grey Level Dependence Matrix, SSD Skewness of spectrum difference Map