A deep learning approach for the early diagnosis of Parkinson's disease using brain MRI scans. (12th April 2022)

• Record Type: Journal Article
• Authors: Mishra, Rishik; Jalal, Anand Singh; Kumar, Manoj; Jalal, Sunita
• Is Part Of: International journal of applied pattern recognition. Volume 7:Number 1(2022)
• Page Start: 64
• Page End: 77
• Publication Date: 2022-04-12
• Subjects: computer-aided diagnosis -- magnetic resonance imaging -- MRI -- deep learning -- Parkinson's disease -- PD -- image processing -- convolution neural networks -- CNN; Pattern perception -- Periodicals; Pattern recognition systems -- Periodicals; 006.405
• Languages: English
• ISSNs: 2049-887X

Abstract

Parkinson's disease (PD) is a neurological disorder with more than six million people worldwide suffering from it. It is commonly diagnosed using clinical assessments and progression scale, which usually depends on the medical practitioner's expertise, and accuracy varies greatly between various examiners which also takes a long time to accurately diagnose. This paper proposes to develop a computer-aided diagnostic method to diagnose PD patients using MRI images of the brain, thus reducing cross-examiner variability and the time required to accurately differentiate between PD and control subjects. We have developed a CNN-based CAD system that classifies between PD and healthy patients, by utilising the differences between the Substantia Nigra region of the brain. The method proposed in this paper was successfully able to achieve an accuracy of 99.5%.