Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography

Understand

The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems.

• Here, we develop a deep learning algorithm that can accurately detect breast cancer on screening mammograms using an "end-to-end" training approach that efficiently leverages training datasets with either complete clinical annotation or only the cancer status (label) of the whole image.
• In this approach, lesion annotations are required only in the initial training stage, and subsequent stages require only image-level labels, eliminating the reliance on rarely available lesion annotations.
• Our all convolutional network method for classifying screening mammograms attained excellent performance in comparison with previous methods.