Brain functional network reconstruction based on compressed sensing and fast iterative shrinkage-thresholding algorithm / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 855-862, 2020.
Article
in Chinese
| WPRIM
| ID: wpr-879213
ABSTRACT
The construction of brain functional network based on resting-state functional magnetic resonance imaging (fMRI) is an effective method to reveal the mechanism of human brain operation, but the common brain functional network generally contains a lot of noise, which leads to wrong analysis results. In this paper, the least absolute shrinkage and selection operator (LASSO) model in compressed sensing is used to reconstruct the brain functional network. This model uses the sparsity of
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Image Processing, Computer-Assisted
/
Brain
/
Magnetic Resonance Imaging
Type of study:
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2020
Type:
Article
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