Table 2.

The morphological and texture features employed for tumor classification.

Category	Feature	Code	Description
Texture	Autocorrelation [30]	TF1	Twenty texture features (TF1–TF20) are extracted from GLCM matrices computed using four distances (d = 1,2, 3,4 pixels) and four orientations (θ = 0°, 45°, 90°, 135°)
	Contrast [12]	TF2
	Correlation [30]	TF3
	Cluster prominence [30]	TF4
	Cluster shade [30]	TF5
	Dissimilarity [30]	TF6
	Energy [30]	TF7
	Entropy [30]	TF8
	Homogeneity [30]	TF9
	Maximum probability [30]	TF10
	Sum of squares [27]	TF11
	Sum average [27]	TF12
	Sum entropy [27]	TF13
	Sum variance [27]	TF14
	Difference variance [27]	TF15
	Difference entropy [27]	TF16
	Information measure of correlation I [27]	TF17
	Information measure of correlation II [27]	TF18
	Inverse difference normalized [31]	TF19
	Inverse difference moment normalized [31]	TF20
Morphological	Tumor area [20]	MF1	Ten morphological features (MF1–MF10) are extracted directly from the tumor
	Perimeter [20]	MF2
	Form factor [13, 17]	MF3
	Roundness [13, 17]	MF4
	Aspect ratio [13, 17]	MF5
	Convexity [13, 17]	MF6
	Solidity [13, 17]	MF7
	Extent [13, 17]	MF8
	Undulation characteristics [21]	MF9
	Compactness [20, 29]	MF10
Morphological	Length of the ellipse major axis [20]	MF11	Six morphological features (MF11–MF16) are extracted from the best-fit ellipse that approximates the size and position of the tumor
	Length of the ellipse minor axis [20]	MF12
	Ratio between the ellipse major and minor axes [20]	MF13
	Ratio of the ellipse perimeter and the tumor perimeter [20]	MF14
	Overlap between the ellipse and the tumor [20]	MF15
	Angle of the ellipse major axis [20]	MF16
Morphological	NRL entropy [18, 20]	MF17	Two morphological features (MF17-MF18) are extracted from the NRL of the tumor
	NRL variance [18, 20]	MF18