Table 1.

Quantitative BI-RADS features

Category	Feature	Description
Shape	Tumor_a, Tumor_p	Tumor area (Tumor_a) and tumor perimeter (Tumor_p) [14]
	Ellipse_a, Ellipse_b, Ellipse_a/b	The length of the major axis (a) and minor axis (b) of the best-fit ellipse [14]
	Ep/Tp	The ratio of the ellipse perimeter (Ep) and the tumor perimeter (Tp) [14]
	Ellipse_compactness	The overlap between the tumor area and the ellipse area [14]
	NRL entropy, NRL variance	The statistics of the distances between boundary points and tumor center
	Compactness	Tumor roundness [22]
Orientation	Ellipse_theta	The angle between the major axis of the best-fit ellipse and the horizontal line [14]
Margin	Undulation, Sharp, MU	The number of undulations on tumor boundary [13]
	NS	The number of spicules on tumor boundary
	MNS	NS × Compactness
	MaxSpicule	Length of the longest spicule of NS
Lesion boundary	LB	Intensity difference around tumor boundary [13]
Echo pattern	EPc	Intensity difference between the 25 % brighter pixels and whole tumor pixels [13]
	EP_diff	Intensity difference between the tumor and the surrounding tissues
	Energy avg., Energy std., Entropy avg., Entropy std., Correlation avg., Correlation std., Inverse Difference Moment avg., Inverse Difference Moment std., Inertia avg., Inertia std., Cluster Shade avg., Cluster Shade std., Cluster Prominence avg., Cluster Prominence std., Haralick Correlation avg., Haralick Correlation std.	16 GLCM texture features [23], the statistics of the correlations between neighbor pixels
Posterior acoustic features	PS	The average intensity difference between the tumor and the region under the tumor [13]
	PS_diff	The average intensity difference between the surrounding tissues and the region under the tumor