Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers

Year : 2025 | Volume : 16 | Issue : 01 | Page : 55 66
    By

    S. Sumahasan,

  • K. Purushotam Naidu,

  • V. Lakshmana Rao,

  • A. Udaya Kumar,

  1. Student, Department of Computer Science and Engineering, Gayatri Vidya Parishad for women, Visakhapatnam, Andhra Pradesh, India
  2. Assistant Professor, Department of Computer Science and Engineering (Artificial Intelligence and Machine Learning), Gayatri Vidya Parishad for women, Visakhapatnam, Andhra Pradesh, India
  3. Student, Department of Computer Science and Engineering, Gayatri Vidya Parishad for women, Visakhapatnam, Andhra Pradesh, India
  4. Student, Department of Computer Science and Engineering, Gayatri Vidya Parishad for women, Visakhapatnam, Andhra Pradesh, India

Abstract

In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based CNN model achieves improved accuracy in PD detection, along with notable precision, recall, and f1-score evaluations. The results of this study emphasize the potential benefits of merging deep learning methodologies with ensemble techniques for reliable PD detection. Through the incorporation of CNNs with meta-classifiers, a hopeful route is introduced for non-invasive and precise identification of PD. This progress holds potential for enhancing patient outcomes and optimizing the efficacy of PD management protocols.

Keywords: Parkinson’s disease, convolutional neural network (CNN), meta-classifiers, handwritten spiral images, VGG16, ResNet50

[This article belongs to Journal of Computer Technology & Applications ]

How to cite this article:
S. Sumahasan, K. Purushotam Naidu, V. Lakshmana Rao, A. Udaya Kumar. Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers. Journal of Computer Technology & Applications. 2024; 16(01):55-66.
How to cite this URL:
S. Sumahasan, K. Purushotam Naidu, V. Lakshmana Rao, A. Udaya Kumar. Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers. Journal of Computer Technology & Applications. 2024; 16(01):55-66. Available from: https://journals.stmjournals.com/jocta/article=2024/view=191741


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Regular Issue Subscription Review Article
Volume 16
Issue 01
Received 05/10/2024
Accepted 04/11/2024
Published 31/12/2024
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