Research on the application of convolution neural network in the diagnosis of Alzheimer's disease.
10.7507/1001-5515.202007019
- Author:
Baohong XU
1
,
2
;
Chong DING
1
,
2
;
Guizhi XU
1
,
2
Author Information
1. Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, P.R.China
2. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, P.R.China.
- Publication Type:Systematic Review
- Keywords:
Alzheimer's disease;
brain imaging;
convolutional neural network;
mild cognitive impairment
- MeSH:
Alzheimer Disease/diagnostic imaging*;
Cognitive Dysfunction/diagnosis*;
Humans;
Image Processing, Computer-Assisted;
Magnetic Resonance Imaging;
Neural Networks, Computer
- From:
Journal of Biomedical Engineering
2021;38(1):169-177
- CountryChina
- Language:Chinese
-
Abstract:
With the wide application of deep learning technology in disease diagnosis, especially the outstanding performance of convolutional neural network (CNN) in computer vision and image processing, more and more studies have proposed to use this algorithm to achieve the classification of Alzheimer's disease (AD), mild cognitive impairment (MCI) and normal cognition (CN). This article systematically reviews the application progress of several classic convolutional neural network models in brain image analysis and diagnosis at different stages of Alzheimer's disease, and discusses the existing problems and gives the possible development directions in order to provide some references.
