DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI.

Journal: Journal of neuroscience methods
Published Date:

Abstract

BACKGROUND: Resting state fMRI has emerged as a popular neuroimaging method for automated recognition and classification of brain disorders. Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common brain disorders affecting young children, yet its underlying mechanism is not completely understood and its diagnosis is mainly dependent on behaviour analysis.

Authors

  • Atif Riaz
    City University of London, Northampton Square, London EC1V 0HB, UK.
  • Muhammad Asad
    City, University of London, London, United Kingdom.
  • Eduardo Alonso
  • Greg Slabaugh
    Digital Environment Research Institute, Queen Mary University of London, London, United Kingdom.