Comparison Analysis of GLCM and PCA on Parkinson's Disease Using Structural MRI

Sanjana Tomer, Ketna Khanna, Sapna Gambhir and Mohit Gambhir
Additional contact information
Sanjana Tomer: J. C. Bose University of Science and Technology, YMCA, India
Ketna Khanna: J. C. Bose University of Science and Technology, YMCA, India
Sapna Gambhir: J. C. Bose University of Science and Technology, YMCA, India
Mohit Gambhir: Innovation Cell, Ministry of Education, Faridabad, India

International Journal of Information Retrieval Research (IJIRR), 2022, vol. 12, issue 1, 1-15

Abstract: Parkinson disease (PD) is a neurological disorder where the dopaminergic neurons experience deterioration. It is caused from the death of the dopamine neurons present in the substantia nigra i.e., the mid part of the brain. The symptoms of this disease emerge slowly, the onset of the earlier stages shows some non-motor symptoms and with time motor symptoms can also be gauged. Parkinson is incurable but can be treated to improve the condition of the sufferer. No definite method for diagnosing PD has been concluded yet. However, researchers have suggested their own framework out of which MRI gave better results and is also a non-invasive method. In this study, the MRI images are used for extracting the features. For performing the feature extraction techniques Gray Level Co-occurrence Matrix and Principal Component Analysis are performed and are analysed. Feature extraction reduces the dimensionality of data. It aims to reduce the feature of data by generating new features from the original one.

Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIRR.289577 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jirr00:v:12:y:2022:i:1:p:1-15

Access Statistics for this article

International Journal of Information Retrieval Research (IJIRR) is currently edited by Zhongyu Lu

More articles in International Journal of Information Retrieval Research (IJIRR) from IGI Global
Bibliographic data for series maintained by Journal Editor ().