Quantifying the impact of Pyramid Squeeze Attention mechanism and filtering approaches on Alzheimer's disease classification.

Yan, Bin; Li, Yang; Li, Lin; Yang, Xiaocheng; Li, Tie-Qiang; Yang, Guang; Jiang, Mingfeng

Yan, Bin; Li, Yang; Li, Lin; Yang, Xiaocheng; Li, Tie-Qiang; Yang, Guang; Jiang, Mingfeng.

Afiliação

Yan B; School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Li Y; School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Li L; School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Yang X; School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China.
Li TQ; Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 171 77, Stockholm, Sweden. Electronic address: tie-qiang.li@ki.se.
Yang G; Cardiovascular Research Centre, Royal Brompton Hospital, London, SW3 6NP, UK; National Heart and Lung Institute, Imperial College London, London, SW7 2AZ, UK. Electronic address: g.yang@imperial.ac.uk.
Jiang M; School of Computer Science and Technology, Zhejiang Sci-Tech University, Hangzhou, 310018, China. Electronic address: m.jiang@zstu.edu.cn.

Comput Biol Med ; 148: 105944, 2022 09.

Article em En | MEDLINE | ID: mdl-35969934

Assuntos

Doença de Alzheimer; Encéfalo; Humanos; Imageamento por Ressonância Magnética; Testes de Estado Mental e Demência; Redes Neurais de Computação

Palavras-chave

Alzheimer's disease; Fully convolutional network; Image classification; Image filtering; Pyramid squeeze attention mechanism

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doença de Alzheimer Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: Comput Biol Med Ano de publicação: 2022 Tipo de documento: Article

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