Artificial Intelligence in medical imaging practice: looking to the future.

Journal: Journal of medical radiation sciences
Published Date: Nov 10, 2019

Abstract

Artificial intelligence (AI) is heralded as the most disruptive technology to health services in the 21 century. Many commentary articles published in the general public and health domains recognise that medical imaging is at the forefront of these changes due to our large digital data footprint. Radiomics is transforming medical images into mineable high-dimensional data to optimise clinical decision-making; however, some would argue that AI could infiltrate workplaces with very few ethical checks and balances. In this commentary article, we describe how AI is beginning to change medical imaging services and the innovations that are on the horizon. We explore how AI and its various forms, including machine learning, will challenge the way medical imaging is delivered from workflow, image acquisition, image registration to interpretation. Diagnostic radiographers will need to learn to work alongside our 'virtual colleagues', and we argue that there are vital changes to entry and advanced curricula together with national professional capabilities to ensure machine-learning tools are used in the safest and most effective manner for our patients.

Authors

  • Sarah J Lewis
    Discipline of Medical Imaging Science, The University of Sydney, Lidcombe, New South Wales, Australia.
  • Ziba Gandomkar
    Image Optimisation and Perception, Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia. Electronic address: ziba.gandomkar@sydney.edu.au.
  • Patrick C Brennan
    Image Optimisation and Perception, Discipline of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia.

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