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Detecting Neurodegenerative Disease from MRI: A Brief Review on a Deep Learning Perspective

  • Manan Binth Taj Noor
  • Nusrat Zerin Zenia
  • M. Shamim KaiserEmail author
  • Mufti MahmudEmail author
  • Shamim Al Mamun
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11976)

Abstract

Rapid development of high speed computing devices and infrastructure along with improved understanding of deep machine learning techniques during the last decade have opened up possibilities for advanced analysis of neuroimaging data. Using those computing tools Neuroscientists now can identify Neurodegenerative diseases from neuroimaging data. Due to the similarities in disease phenotypes, accurate detection of such disorders from neuroimaging data is very challenging. In this article, we have reviewed the methodological research papers proposing to detect neurodegenerative diseases using deep machine learning techniques only from MRI data. The results show that deep learning based techniques can detect the level of disorder with relatively high accuracy. Towards the end, current challenges are reviewed and some possible future research directions are provided.

Keywords

Machine learning Alzheimer’s disease Schizophrenia Parkinson’s disease MRI 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Institute of Information TechnologyJahangirnagar UniversityDhakaBangladesh
  2. 2.Department of Computing and TechnologyNottingham Trent UniversityNottinghamUK

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