Segmentation of Breast Masses in Digital Mammography Based on U-Net Deep Convolutional Neural Networks

In this paper, we propose a new algorithm for segmentation of breast masses in digital mammography based on U-Net deep convolutional neural networks. All raw mammogram images are preprocessed to improve segmentation reliability. Deep learning was carried out using additional methods of data augmentation and fine tuning of the neural network. The performance of the proposed algorithm for segmentation of breast masses using the known CBIS-DDSM database is discussed.