Clinical Artificial Intelligence Applications: Breast Imaging.

Journal: Radiologic clinics of North America
Published Date:

Abstract

This article gives a brief overview of the development of artificial intelligence in clinical breast imaging. For multiple decades, artificial intelligence (AI) methods have been developed and translated for breast imaging tasks such as detection, diagnosis, and assessing response to therapy. As imaging modalities arise to support breast cancer screening programs and diagnostic examinations, including full-field digital mammography, breast tomosynthesis, ultrasound, and MRI, AI techniques parallel the efforts with more complex algorithms, faster computers, and larger data sets. AI methods include human-engineered radiomics algorithms and deep learning methods. Examples of these AI-supported clinical tasks are given along with commentary on the future.

Authors

  • Qiyuan Hu
    Committee on Medical Physics, Department of Radiology, The University of Chicago, 5841 S Maryland Ave., Chicago, IL, MC202660637, USA. qhu@uchicago.edu.
  • Maryellen L Giger
    Department of Radiology, University of Chicago, 5841 S Maryland Ave., Chicago, IL, 60637, USA.