Feature Fusion Based on Convolutional Neural Network for Breast Cancer Auxiliary Diagnosis

Table 3

Comparison of the correct rate of the VIRNets model using the BreaKHis test set and different architectures.

Structure	Accuracy under different magnifications				Average accuracy (%)
	40X (%)	100X (%)	200X (%)	400X (%)
CSDCNN [19]	95.9	96.9	96.7	94.9	96.1
IRRCNN [20]	97.95	97.57	97.32	97.36	97.55
Bi-LSTM [21]	96.2	97.2	97.1	95.4	96.48
BreastNet [22]	97.99	97.84	98.51	95.88	97.55
Sharma et al. [23]	97.4	98.6	97.7	96.8	97.63
VIRNets (ours)	99.02	97.62	98.02	98.37	98.26