Machine-learning in grading of gliomas based on multi-parametric magnetic resonance imaging at 3T.

Journal: Computers in biology and medicine
Published Date: Jun 15, 2018

Abstract

OBJECTIVE: The objective of this study was to assess the contribution of multi-parametric (mp) magnetic resonance imaging (MRI) quantitative features in the machine learning-based grading of gliomas with a multi-region-of-interests approach.

Authors

  • Fusun Citak-Er
    Department of Computer Programming, Pîrî Reis University, Istanbul, Turkey; Department of Biotechnology, Yeditepe University, Istanbul, Turkey. Electronic address: fusun.er@gmail.com.
  • Zeynep Firat
    Department of Radiology, Yeditepe University Hospital, Istanbul, Turkey.
  • Ilhami Kovanlikaya
    Department of Radiology, Weill Cornell Medical College, New York, NY, USA.
  • Ugur Ture
    Department of Neurosurgery, Yeditepe University Hospital, Istanbul, Turkey.
  • Esin Ozturk-Isik
    Biomedical Engineering Institute, Boğaziçi University, Istanbul, Turkey.

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