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.
Artigo
em Chinês
| 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
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Processamento de Imagem Assistida por Computador
/
Encéfalo
/
Imageamento por Ressonância Magnética
Tipo de estudo:
Estudo prognóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2020
Tipo de documento:
Artigo
Similares
MEDLINE
...
LILACS
LIS