Deep Learning Based Diagnosis of Parkinson's Disease Using CNN

Authors

  • Dr. Shubhangi D C  Chairman & Professor, Department of Studies in Computer Science and Engineering, VTU, CPGS, Kalaburagi, Karnataka, India
  • Pooja Gundagurti  Student, Department of Studies in Computer Science and Engineering, VTU, CPGS, Kalaburagi, Karnataka, India

DOI:

https://doi.org/10.32628/CSEIT2062105

Keywords:

Parkinson's disease, MRI, Deep learning, Convolutional neural networks, AlexNet

Abstract

Parkinson's disease is the degenerative disease caused by loss of dopamine producing neurons. PD is characterized by gradual degradation of motor function in the brain. In this, deep learning is used to diagnose the PD patients by means of Convolutional Neural Networks (CNN). The CNN architecture ALexNet is used to refine the diagnosis of Parkinson’s disease. The MR images are trained by the transfer learned network along with the KNN algorithm to give the accuracy measures.

References

  1. S. Sivaranjini, C. M. Sujatha “Deep learning based diagnosis of Parkinson’s disease using convolutional neural network” Dept. of E&CE, Anna University, Chennai, March 21, 2019
  2. Shivangi, Anubhav Johri, Ashish Tripathi “Parkinson Disease Detection Using Deep Neural Networks” Dept. of Computer Science, Jaypee Institute of IT, Noida, 2019
  3. Shu Lih Oh, Yuki Hagiwara, U. Raghavendra, Rajamanickam Yuvaraj, N. Arunkumar, M. Murugappan, U. Rajendra Acharya “A deep learning approach for Parkinson’s disease diagnosis from EEG signals” Dept. of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore, 30 August 2018
  4. Srishti Gover, Saloni Bhartia, Akshama, Abhilasha Yadav, Seeja K. R “Predicting Severity Of Parkinson’s Disease Using Deep Learning” Dept. of CSE, Indira Gandhi Delhi Technical University foe Women, Delhi, 2018
  5. Clayton R. Pereira, Sike A. T. Weber, Christian Hook, Gustavo H. Rosa, Joao Papa “Deep Learning-aided Parkinson’s Disease Diagnosis from Handwritten Dynamics” Dept. of Computing, Federal University of Sao Carlos, Brazil, June 2016
  6. Ram Deepak Gottapu, Cihan H Dagli “Analysis of Parkinson’s Disease Data” Missouri University of Science and Technology, USA, November 2018
  7. Dag Aarsland “Cognitive impairement in Parkinson’s disease and dementia with Lewy bodies” Karolinsha Institutet, Dept NVS, Center for Alzheimer Research, Sweden, January 2016
  8. Chaudhari KR, Healy DG, Schapira “Non-motor symptoms of Parkinson’s disease: diagnosis and management” National Institute for Clinical Excellence, March 2006
  9. Ozkan Cigdem, Arif Yilmaz, Iman Beheshti, Hasan Demirel “Comparing the performances of PDF and PCA on Parkinson’s disease classification using structural MRI images” Dept. of E&EE, Eastern Mediterranean University, Turkey, May 1, 2018
  10. Cheng HC, Christina M Ulane, Robert E Burke “Clinical progression in Parkinson’s disease and the neurobiology of axons” Annals of neurobiology, June 2010
  11. Dan Long, Jinwei Wang, Min Xuan, Quanquan Gu, Xiaojun Xu, Dexing Kong, Minming Zhang “ Automatic Classification of Early Parkinson’s Disease with Multi-Modal MR Imaging” Dept. of Radiology, Zhejiang University School of Medicine, China, November 9, 2012
  12. Xingfeng Li, Yue Xing, Stefan T Schwarz, Dorothee P. Auer “Limbic Grey Matter Changes in Early Parkinson’s Disease” Radiological Sciences, University of Nottingham, Queen’s Medical Centre, United Kingdom, 2017
  13. Athanasios Tagaris, Dimitrios Kollias, Andreas Stafylopatis “Assessment of Parkinson’s Disease Based on Deep Neural Networks” School of Electrical & Computer Engineering, National Technical University of Athens, Greece, August 2, 2017
  14. C. Salvatore, A. Cerasa, I. Castiglioni, F. Gallivanone, A. Augimeri, M. Lopez, G. Arabia, M. Morelli, M. C. Gilardi, A. Quattrone “Machine Learning on Brain MRI data for differential diagnosis of Parkinson’s disease and Progressive Supranuclear Palsy” Dept. of Physics, University of Milan Bicocca, Italy, January 30, 2014
  15. Tamara Pringsheim, Nathalie Jette, Alexandra Frolkies, Thomas D. L. Steeves “The prevalence of Parkinson’s disease: a systematic review and meta-analysis”, The University of Calgary, Canada, November 2014

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

Downloads

Published

2020-04-30

Issue

Volume 6, Issue 2, March-April-2020

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Dr. Shubhangi D C, Pooja Gundagurti, " Deep Learning Based Diagnosis of Parkinson's Disease Using CNN" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 2, pp.351-355, March-April-2020. Available at doi : https://doi.org/10.32628/CSEIT2062105