Computer-aided detection of abnormality in mammography using deep object detectors

Abstract Computer-aided detection of medical abnormalities is of great importance for both doctors and patients. In this chapter, we use mammogram screening as an example and introduce two state-of-the-art deep neural networks for the detection of mass tissues. More specifically, we compare two-stage and one-stage object detectors using deep convolutional neural networks. With the limited number of training data, we use transfer learning to fine-tune the general object detectors on a publicly available mammogram dataset. Experimental results indicate that the deep learning-based approaches have great potential in mammogram screening.