Artificial intelligence, machine (deep) learning and radio(geno)mics: definitions and nuclear medicine imaging applications.

Journal: European journal of nuclear medicine and molecular imaging
Published Date:

Abstract

Techniques from the field of artificial intelligence, and more specifically machine (deep) learning methods, have been core components of most recent developments in the field of medical imaging. They are already being exploited or are being considered to tackle most tasks, including image reconstruction, processing (denoising, segmentation), analysis and predictive modelling. In this review we introduce and define these key concepts and discuss how the techniques from this field can be applied to nuclear medicine imaging applications with a particular focus on radio(geno)mics.

Authors

  • Dimitris Visvikis
    LaTIM, INSERM, UMR 1101, Brest 29609, France.
  • Catherine Cheze Le Rest
    DACTIM University of Poitiers, Nuclear Medicine Department, CHU Milétrie, Poitiers 86021, France.
  • Vincent Jaouen
    LaTIM, INSERM UMR 1101, IBRBS, Faculty of Medicine, Univ Brest, 22 avenue Camille Desmoulins, 29238, Brest, France.
  • Mathieu Hatt
    LaTIM, INSERM, UMR 1101, Brest 29609, France.