Radiomics for classification of bone mineral loss: A machine learning study.

Journal: Diagnostic and interventional imaging
Published Date:

Abstract

PURPOSE: The purpose of this study was to develop predictive models to classify osteoporosis, osteopenia and normal patients using radiomics and machine learning approaches.

Authors

  • S Rastegar
    Student Research Committee, School of Paramedical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran; Department of Radiology Technology, School of Paramedical Sciences, Rafsanjan University of Medical Sciences, Rafsanjan, Iran.
  • M Vaziri
    Student Research Committee, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran; Department of Radiologic Sciences, Medical Physics, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran.
  • Y Qasempour
    Student Research Committee, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran; Department of Radiologic Sciences, Medical Physics, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran.
  • M R Akhash
    Student Research Committee, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran; Department of Radiologic Sciences, Medical Physics, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran.
  • N Abdalvand
    Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
  • I Shiri
    Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland.
  • H Abdollahi
    Student Research Committee, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran; Department of Radiologic Sciences, Medical Physics, Faculty of Allied Medicine, Kerman University of Medical Sciences, Kerman, Iran. Electronic address: hamid_rbp@yahoo.com.
  • H Zaidi
    Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland; Geneva University Neurocenter, Geneva University, CH-1205 Geneva, Switzerland; Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, The Netherlands; Department of Nuclear Medicine, University of Southern Denmark, 5230 Odense, Denmark.