Automated Quality Assessment of Structural Magnetic Resonance Brain Images Based on a Supervised Machine Learning Algorithm.

Journal: Frontiers in neuroinformatics
Published Date: Dec 19, 2016

Abstract

High-resolution three-dimensional magnetic resonance imaging (3D-MRI) is being increasingly used to delineate morphological changes underlying neuropsychiatric disorders. Unfortunately, artifacts frequently compromise the utility of 3D-MRI yielding irreproducible results, from both type I and type II errors. It is therefore critical to screen 3D-MRIs for artifacts before use. Currently, quality assessment involves slice-wise visual inspection of 3D-MRI volumes, a procedure that is both subjective and time consuming. Automating the quality rating of 3D-MRI could improve the efficiency and reproducibility of the procedure. The present study is one of the first efforts to apply a support vector machine (SVM) algorithm in the quality assessment of structural brain images, using global and region of interest (ROI) automated image quality features developed in-house. SVM is a supervised machine-learning algorithm that can predict the category of test datasets based on the knowledge acquired from a learning dataset. The performance (accuracy) of the automated SVM approach was assessed, by comparing the SVM-predicted quality labels to investigator-determined quality labels. The accuracy for classifying 1457 3D-MRI volumes from our database using the SVM approach is around 80%. These results are promising and illustrate the possibility of using SVM as an automated quality assessment tool for 3D-MRI.

Authors

  • Ricardo A Pizarro
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; Department of Biomedical Engineering, UW-MadisonMadison, WI, USA.
  • Xi Cheng
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; The Lieber Institute for Brain DevelopmentBaltimore, MD, USA; Bioinformatics and Computational Biosciences Branch, Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Diseases (NIAID), National Institutes of HealthRockville, MD, USA.
  • Alan Barnett
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of Health Bethesda, MD, USA.
  • Herve Lemaitre
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; NeuroImaging and Psychiatry, UMR 1000, Faculté de Médecine, Institut National de la Santé Et de la Recherche Médicale, Service Hospitalier Frédéric Joliot, Université Paris-SudOrsay, France.
  • Beth A Verchinski
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; The Lieber Institute for Brain DevelopmentBaltimore, MD, USA.
  • Aaron L Goldman
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; The Lieber Institute for Brain DevelopmentBaltimore, MD, USA.
  • Ena Xiao
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; The Lieber Institute for Brain DevelopmentBaltimore, MD, USA.
  • Qian Luo
    Behavioral Biology Branch, Walter Reed Army Research Institute Silver Spring, MD, USA.
  • Karen F Berman
    Clinical and Translational Neuroscience Branch, National Institute of Mental Health, National Institutes of Health Bethesda, MD, USA.
  • Joseph H Callicott
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; Clinical and Translational Neuroscience Branch, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA.
  • Daniel R Weinberger
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; The Lieber Institute for Brain DevelopmentBaltimore, MD, USA; Departments of Psychiatry, Neurology and Neuroscience, Johns Hopkins University School of MedicineBaltimore, MD, USA; The Institute of Genetic Medicine, Johns Hopkins University School of MedicineBaltimore, MD, USA.
  • Venkata S Mattay
    Genes, Cognition, and Psychosis Program, National Institute of Mental Health, National Institutes of HealthBethesda, MD, USA; The Lieber Institute for Brain DevelopmentBaltimore, MD, USA; Departments of Neurology and Radiology, Johns Hopkins University School of MedicineBaltimore, MD, USA.

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