Machine learning: from radiomics to discovery and routine.

Journal: Der Radiologe
Published Date:

Abstract

Machine learning is rapidly gaining importance in radiology. It allows for the exploitation of patterns in imaging data and in patient records for a more accurate and precise quantification, diagnosis, and prognosis. Here, we outline the basics of machine learning relevant for radiology, and review the current state of the art, the limitations, and the challenges faced as these techniques become an important building block of precision medicine. Furthermore, we discuss the roles machine learning can play in clinical routine and research and predict how it might change the field of radiology.

Authors

  • G Langs
    Department of Biomedical Imaging and Image-Guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Währinger Gürtel 18-20, 1090, Vienna, Austria. georg.langs@meduniwien.ac.at.
  • S Röhrich
  • J Hofmanninger
  • F Prayer
  • J Pan
  • C Herold
  • H Prosch