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Traditional breast cancer image classification methods require manualextraction of features from medical images, which not only require professionalmedical knowledge, but also have problems such as time-consuming andlabor-intensive and difficulty in extracting high-quality features. Therefore,the paper proposes a computer-based feature fusion Convolutional neural networkbreast cancer image classification and detection method. The paper pre-trainstwo convolutional neural networks with different structures, and then uses theconvolutional neural network to automatically extract the characteristics offeatures, fuse the features extracted from the two structures, and finally usethe classifier classifies the fused features. The experimental results showthat the accuracy of this method in the classification of breast cancer imagedata sets is 89%, and the classification accuracy of breast cancer images issignificantly improved compared with traditional methods.

Research on the Detection Method of Breast Cancer Deep Convolutional Neural Network Based on Computer Aid