Brain Disease Classification Along with Age Estimation from MRI

Project Code :TCMAPY496

Objective

The main objective of this to predict the brain MRI scanned images either they are normal or effected with disease along with the age estimations using deep learning and machine learning algorithms.

Abstract

Chronological age of healthy people is able to be predicted accurately using deep neural networks from neuroimaging data, and the predicted brain age could serve as a biomarker for detecting aging-related diseases. Hence, in this proposed method we are using the cascade network of the deep learning which is a Convolutional Neural Network (CNN) and also one of the machine learning algorithm named Support Vector Machine (SVM). These algorithms are been used to train the brain  MRI images which are considered in the three classes as the Normal which is not affected with any disease and the other classes which were affected with Alzheimer’s disease (AD) and Mild Cognitive Impairment (MCI). From which we can also find out the ages from the classified images. CNN and SVM are mainly used for the training of the MRI image dataset, upon where the classification will be performed along with the age estimation.

Keywords: Age estimation, Alzheimer’s disease (AD) and Mild Cognitive Impairment, CNN, deep learning, SVM, machine learning.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W Configuration:
  • Processor:  I3/Intel Processor
  • Hard Disk: 160GB 


S/W Configuration:

  • Operating System:  Windows 7/8/10  
  • IDE:  Pycharm 
  • Libraries Used:   Numpy, IO, OS, Keras
  • Technology:  Python 3.6+

Learning Outcomes

  •          Testing techniques
  •          Error correction mechanisms
  •          What type of technology versions is used?
  •          Working of Tensor Flow
  •          Implementation of Deep Learning techniques
  •          Implementation of Machine Learning techniques
  •          Working of CNN algorithm
  •          Working of SVM algorithm
  •          Building of model creations
  •          Scope of project
  •          Applications of the project
  •          About Python language
  •          About Deep Learning Frameworks
  •          Use of Data Science
  •        Practical exposure to

o   Hardware and software tools

o   Solution providing for real time problems

o   Working with team/individual

o   Work on creative ideas

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