Brain pathology identification using computer aided diagnostic tool: A systematic review.

Journal: Computer methods and programs in biomedicine
Published Date: Apr 1, 2020

Abstract

Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-of-life by reducing human errors in diagnosis. CAD can expedite decision-making on complex clinical data automatically. Since brain diseases can be fatal, rapid identification of brain pathology to prolong patient life is an important research topic. Many algorithms have been proposed for efficient brain pathology identification (BPI) over the past decade. Constant refinement of the various image processing algorithms must take place to expand performance of the automatic BPI task. In this paper, a systematic survey of contemporary BPI algorithms using brain magnetic resonance imaging (MRI) is presented. A summarization of recent literature provides investigators with a helpful synopsis of the domain. Furthermore, to enhance the performance of BPI, future research directions are indicated.

Authors

  • Anjan Gudigar
    Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
  • U Raghavendra
    Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India. Electronic address: raghavendra.u@manipal.edu.
  • Ajay Hegde
    Neurosurgery, Institute of Neurological Sciences, NHS Greater Glasgow and Clyde, Glasgow, United Kingdom.
  • M Kalyani
    Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.
  • Edward J Ciaccio
    Department of Medicine, Celiac Disease Center, Columbia University, New York, USA.
  • U Rajendra Acharya
    Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore; Department of Biomedical Engineering, School of Science and Technology, SUSS University, Clementi 599491, Singapore; International Research Organization for Advanced Science and Technology (IROAST), Kumamoto University, Kumamoto, Japan.

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