Clustering fMRI data with a robust unsupervised learning algorithm for neuroscience data mining.

Journal: Journal of neuroscience methods
Published Date: Feb 20, 2018

Abstract

BACKGROUND: Clustering approaches used in functional magnetic resonance imaging (fMRI) research use brain activity to divide the brain into various parcels with some degree of homogeneous characteristics, but choosing the appropriate clustering algorithms remains a problem.

Authors

  • Hadeel K Aljobouri
    Electrical and Electronics Engineering Department, Graduate School of Natural Science, Ankara Yıldırım Beyazıt University, Ankara, Turkey; Biomedical Engineering Department, College of Engineering, Al-Nahrain University, Baghdad, Iraq. Electronic address: hadeel_bme77@eng.nahrainuniv.edu.iq.
  • Hussain A Jaber
    Electrical and Electronics Engineering Department, Graduate School of Natural Science, Ankara Yıldırım Beyazıt University, Ankara, Turkey.
  • Orhan M Koçak
    Psychiatry Department, School of Medicine, Kırıkkale University, Kırıkkale, Turkey.
  • Oktay Algin
    Department of Radiology, Ataturk Training and Research Hospital, Ankara Yıldırım Beyazıt University, Ankara, Turkey; National MR Research Center, Bilkent University, Ankara, Turkey.
  • Ilyas Çankaya
    Electrical and Electronics Engineering Department, Graduate School of Natural Science, Ankara Yıldırım Beyazıt University, Ankara, Turkey.

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