Medical Journal of Mashhad university of Medical Sciences

Medical Journal of Mashhad university of Medical Sciences

Diagnosis and classification of Alzheimer's disease by 3 D Residual Block

Document Type : Research Paper

Authors
Firouzeh Razavi 1
Mohammad Jafar Tarekh 2
Mahmood Alborzi 1
1 Department of Information Technology Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
2 Department of Industrial Engineering, K.N. Toosi University of Technology, Tehran, Iran
10.22038/mjms.2019.14993
Abstract
abstract
Introduction: In recent years, many studies have been done to analyze brain diseases in order to identify brain diseases that have a significant role in creating diagnostic intelligent systems. among the different methods of machine learning, deep learning based methods in recent years have been a wide application of the development of intelligent systems, which resulted in the creation of powerful systems for diagnosis of disease.
Method: In this study, the diagnosis of Alzheimer's patients with deep learning neural network is based on method of 3- D Residual  Block. the training and test procedure presented by ADNI data set  
Results: The results showed that the output of this Method were conducted in comparison to the proposed methods, accuracy of diagnose and classification of Alzheimer's disease.
Conclusion: the findings of the present study showed that the machine learning with deep learning methods can diagnose Alzheimer's disease sooner than doctors.
Keywords
Alzheimer's disease
Deep learning
3-Dimensional Residual Block
Medical Journal of Mashhad university of Medical Sciences
Volume 62, Issue 5.1
November and December 2019
Pages 1748-1755