• Parkinson’s Disease (PD) is a progressive neurodegenerative disorder, which is characterized by  Various  symptoms.
  • progressive neurodegenerative disorder affects nervous system in the elderly, which is characterized by motor symptoms such as tremor, rigidity, slowness of movement and problems with gait.
  • In this work, an attempt has been made to classify the spiral images of healthy control and Parkinson’s disease subjects using deep learning neural network.
  • The Vision based Convolutional Neural Network architecture is used to refine the diagnosis of neurodegenerative disorder disease


  • The Brain MRI images are trained and tested to give the accuracy Disease measures.
  • volumetric analysis is one of the widely used MRI protocols to demonstrate pathological modifications related to PD in the striatal region.


  • They system does not give the accurate results .
  • MRI Imaging involves high cost of production.
  • The image resolution is low so the face expression will not be detected.



  • Parkinsons disease (PD) is a progressive neurodegenerative disorder of the nervous system in the elderly.
  • Vision Based methods have reported promising results in providing better characterization of PD in the early stages and are expected to have better sensitivity than standard clinical measures.
  • This project proposes a Vision Based novel deep learning architecture for neuro generative disorder screening.
  • In this project, analysis of MRI images for discrimination of healthy control and NDD (Neurodegenerative disorder) subjects is attempted using CNN model.
  • The proposed FAST-RCNN exploits Feature Extraction to tackle multi-view data from the Spiral Image data.
  • In training, the proposed model employs a data enhancement technology called SCI-KIT’ Image Data Generator API on multi-view data.
  • The data features are enriched by this data augmented technology, which can increase the diversity of the experimental samples.


  • They recognized faster and more accurately
  • The model is trained to learn the low level to high level features and the classification results are validated.
  • Thus with a rapid growth in the deep learning architectures, an objective diagnosis of Parkinson’s disease will no longer be a laborious job for the clinicians in the near future.

Software Requirements:

  • Front End – Anaconda IDE
  • Backend – SQL
  • Language – Python 3.8

Hardware Requirements:

  • Hard Disk: Greater than 500 GB
  • RAM: Greater than 4 GB
  • Processor: I3 and Above