A Novel Algorithm for Breast Mass Classification in Digital Mammography Based on Feature Fusion

Table 4

Comparison of proposed method with other mass classification methods.

Dataset	Methods	Sens	Spec	Acc	AUC
CBIS-DDSM	ResNet50	77.31%	82.07%	79.50%	0.86
	MR8 + ResNet50	83.17%	85.94%	84.50%	0.88
	EfficientNet-B7	80.47%	81.05%	80.75%	0.80
	MR8 + EfficientNet-+B7	89.88%	88.02%	89.30%	0.85
DDSM	M. Hussain et al. [44]	–	–	85.53%	0.87
BCDR	L. Fangyi et al. [45]	88.93%	93.41%	91.65%	0.96
INbreast	N. Dhungel [46]	98.00%	70.00%	90.00%	–
CBIS-DDSM	C. Yuanqin [47]	93.83%	92.17%	93.15%	0.95
DDSM	S. V. da rochaa [10]	85.00%	91.89%	88.31%	0.88
DDSM	Q. Abbas [11]	92.00%	84.20%	91.00%	0.91
CBIS-DDSM	Proposed method	89.97%	97.91%	94.30%	0.97