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Detection and Prediction of Schizophrenia Using Magnetic Resonance Images and Deep Learning

  • S. Srivathsan
  • B. Sreenithi
  • J. NarenEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1040)

Abstract

Researchers are continuously making breakthroughs on the impact of deep learning in the medical industry. This approach of Deep Learning (DL) in neuroimaging creates new insights in modification of brain structures during various disorders, helping capture complex relationships that may not have been visible otherwise. The main aim of proposed work is to effectively detect the presence of schizophrenia, a mental disorder that has drastic implications and is hard to spot, using Magnetic Resonance Image Features from fMRI Database. Dataset is then fed to a Neural Network classifier, which learns to predict and give indications for preventing the onset of Schizophrenia using regression models.

Keywords

Schizophrenia Neural network Deep learning MRI FNC SBM 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.SASTRA Deemed UniversityTirumalaisamudram, ThanjavurIndia

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