A review on brain age prediction in brain ageing.
10.7507/1001-5515.201804030
- Author:
Lan LIN
1
;
Jingxuan WANG
2
;
Zhenrong FU
2
;
Xuetao WU
2
;
Shuicai WU
2
Author Information
1. College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100124, P.R.China.lanlin@bjut.edu.cn.
2. College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100124, P.R.China.
- Publication Type:Journal Article
- Keywords:
brain age;
brain ageing;
convolution neural network;
machine learning;
neuroimage;
prediction model
- MeSH:
Aging;
Brain;
diagnostic imaging;
physiology;
Humans;
Neuroimaging
- From:
Journal of Biomedical Engineering
2019;36(3):493-498
- CountryChina
- Language:Chinese
-
Abstract:
The human brain deteriorates as we age, and the rate and the trajectories of these changes significantly vary among brain regions and among individuals. Because neuroimaging data are potentially important indicators of individual's brain health, they are commonly used in brain age prediction. In this review, we summarize brain age prediction model from neuroimaging-based studies in the last ten years. The studies are categorized based on their image modalities and feature types. The results indicate that the prediction frameworks based on neuroimaging holds promise toward individualized brain age prediction. Finally, we addressed the challenges in brain age prediction and suggested some future research directions.
