TABLE 1.

Comparison of AUC values and corresponding standard deviations of 8 different prediction schemes by using 2 dense breast region segmentation methods.

Feature fusion method	New dense breast region segmentation method	Previous dense breast region segmentation method
Scheme 1 (Taking maximum value of the selected features)	0.603±0.043	0.603±0.043
Scheme 2 (Taking minimum value of the selected features)	0.690±0.040	0.606±0.043
Scheme 3 (Taking mean value of the selected features)	0.640±0.043	0.621±0.043
Scheme 4 (one-stage classification scheme)	0.813±0.034	0.641±0.042
Scheme 5 (asymmetry feature based classifier)	0.807±0.035	0.623±0.043
Scheme 6 (mean feature based classifier)	0.657±0.043	0.603±0.043
Scheme 7 (maximum feature based classifier)	0.704±0.040	0.616±0.043
Scheme 8 (two-stage classification scheme)	0.830±0.033	0.633±0.043