Early diagnosis of Alzheimer's disease based on three-dimensional convolutional neural networks ensemble model combined with genetic algorithm / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 47-55, 2021.
Article
in Chinese
| WPRIM
| ID: wpr-879248
ABSTRACT
The pathogenesis of Alzheimer's disease (AD), a common neurodegenerative disease, is still unknown. It is difficult to determine the atrophy areas, especially for patients with mild cognitive impairment (MCI) at different stages of AD, which results in a low diagnostic rate. Therefore, an early diagnosis model of AD based on 3-dimensional convolutional neural network (3DCNN) and genetic algorithm (GA) was proposed. Firstly, the 3DCNN was used to train a base classifier for each region of interest (ROI). And then, the optimal combination of the base classifiers was determined with the GA. Finally, the ensemble consisting of the chosen base classifiers was employed to make a diagnosis for a patient and the brain regions with significant classification capability were decided. The experimental results showed that the classification accuracy was 88.6% for AD
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Brain
/
Magnetic Resonance Imaging
/
Neural Networks, Computer
/
Neurodegenerative Diseases
/
Early Diagnosis
/
Alzheimer Disease
/
Cognitive Dysfunction
Type of study:
Diagnostic study
/
Prognostic study
/
Screening study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2021
Type:
Article
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