Mammography Classification Based on Convolutional Neural Network
Changjiang Zhang, Huanhuan Nie · 2018
Limited by various conditions, the features of mammography images are difficult to extract, so it is hard to classify them.The paper proposed a method based on deep learning method to classify benign and malignant mammography images.The convolutional neural network concludes four convolution layers, four pool layers, and two full-connection layers, and a Softmax layer.The paper designed a new network architecture to improve the traditional one.As a result, we have done an experiment on the DDSM database.Compared with other classification methods, it shows that the method proposed in this paper is more effective than other methods.