The visual inspection of the neurodegenerative disease through medical imaging is a tedious and error prone task. Most of the times the radiologist can misunderstand the disorder to be normal aging effect. In this project a system is being introduced which automatically classifies the kind of neurodegenerative disease. Basic image processing like preprocessing followed by feature extraction have been done in input Magnetic Resonance Image (MRI).
Neural network methodologies have been used for testing and training the image which is preceded by Gray Level Co Matrix (GLCM). These features undergo a training phase of neural network followed by testing to classify the kind of neurodegenerative disease whether Parkinson or Schizophrenia or Normal. Support Vector Machine (SVM) is the neural networkwhich is opted here.