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Early Diagnosis of Alzheimer’s Disease Based on Convolutional Neural Networks

Atif Mehmood1,*, Ahed Abugabah1, Ahmed Ali AlZubi2, Louis Sanzogni3

1 College of Technological Innovation, Zayed University, Abu Dhabi Campus, FF2-0-056, UAE
2 Computer Science Department, Community College, King Saud University, Riyadh, 11437, Saudi Arabia
3 Nathan Campus, Griffith University, Brisbane, Australia

* Corresponding Author: Atif Mehmood. Email: email

Computer Systems Science and Engineering 2022, 43(1), 305-315. https://doi.org/10.32604/csse.2022.018520

Abstract

Alzheimer’s disease (AD) is a neurodegenerative disorder, causing the most common dementia in the elderly peoples. The AD patients are rapidly increasing in each year and AD is sixth leading cause of death in USA. Magnetic resonance imaging (MRI) is the leading modality used for the diagnosis of AD. Deep learning based approaches have produced impressive results in this domain. The early diagnosis of AD depends on the efficient use of classification approach. To address this issue, this study proposes a system using two convolutional neural networks (CNN) based approaches for an early diagnosis of AD automatically. In the proposed system, we use segmented MRI scans. Input data samples of three classes include 110 normal control (NC), 110 mild cognitive impairment (MCI) and 105 AD subjects are used in this paper. The data is acquired from the ADNI database and gray matter (GM) images are obtained after the segmentation of MRI subjects which are used for the classification in the proposed models. The proposed approaches segregate among NC, MCI, and AD. While testing both methods applied on the segmented data samples, the highest performance results of the classification in terms of accuracy on NC vs. AD are 95.33% and 89.87%, respectively. The proposed methods distinguish between NC vs. MCI and MCI vs. AD patients with a classification accuracy of 90.74% and 86.69%. The experimental outcomes prove that both CNN-based frameworks produced state-of-the-art accurate results for testing.

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APA Style
Mehmood, A., Abugabah, A., AlZubi, A.A., Sanzogni, L. (2022). Early diagnosis of alzheimer’s disease based on convolutional neural networks. Computer Systems Science and Engineering, 43(1), 305-315. https://doi.org/10.32604/csse.2022.018520
Vancouver Style
Mehmood A, Abugabah A, AlZubi AA, Sanzogni L. Early diagnosis of alzheimer’s disease based on convolutional neural networks. Comput Syst Sci Eng. 2022;43(1):305-315 https://doi.org/10.32604/csse.2022.018520
IEEE Style
A. Mehmood, A. Abugabah, A.A. AlZubi, and L. Sanzogni "Early Diagnosis of Alzheimer’s Disease Based on Convolutional Neural Networks," Comput. Syst. Sci. Eng., vol. 43, no. 1, pp. 305-315. 2022. https://doi.org/10.32604/csse.2022.018520



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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