Challenges for machine learning in clinical translation of big data imaging studies.

Journal: Neuron
Published Date:

Abstract

Combining deep learning image analysis methods and large-scale imaging datasets offers many opportunities to neuroscience imaging and epidemiology. However, despite these opportunities and the success of deep learning when applied to a range of neuroimaging tasks and domains, significant barriers continue to limit the impact of large-scale datasets and analysis tools. Here, we examine the main challenges and the approaches that have been explored to overcome them. We focus on issues relating to data availability, interpretability, evaluation, and logistical challenges and discuss the problems that still need to be tackled to enable the success of "big data" deep learning approaches beyond research.

Authors

  • Nicola K Dinsdale
    Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, United Kingdom. Electronic address: nicola.dinsdale@dtc.ox.ac.uk.
  • Emma Bluemke
    Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, United Kingdom.
  • Vaanathi Sundaresan
    Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Oxford-Nottingham Centre for Doctoral Training in Biomedical Imaging, University of Oxford, UK; Oxford India Centre for Sustainable Development, Somerville College, University of Oxford, UK. Electronic address: vaanathi.sundaresan@dtc.ox.ac.uk.
  • Mark Jenkinson
    Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Stephen M Smith
    Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, UK.
  • Ana I L Namburete
    Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, United Kingdom. Electronic address: ana.namburete@eng.ox.ac.uk.