Attention-guided multi-scale context aggregation network for multi-modal brain glioma segmentation.

Wu, Shaozhi; Cao, Yunjian; Li, Xinke; Liu, Qiyu; Ye, Yuyun; Liu, Xingang; Zeng, Liaoyuan; Tian, Miao

Wu, Shaozhi; Cao, Yunjian; Li, Xinke; Liu, Qiyu; Ye, Yuyun; Liu, Xingang; Zeng, Liaoyuan; Tian, Miao.

Afiliação

Wu S; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Cao Y; Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China.
Li X; West China School of Medicine, Sichuan University, Chengdu, China.
Liu Q; Radiology Department, Mianyang Central Hospital, Mianyang, China.
Ye Y; Department of Electrical and Computer Engineering, University of Tulsa, Tulsa, Oklahoma, USA.
Liu X; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Zeng L; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.
Tian M; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China.

Med Phys ; 50(12): 7629-7640, 2023 Dec.

Article em En | MEDLINE | ID: mdl-37151131

Assuntos

Neoplasias Encefálicas; Glioma; Ácido Tranexâmico; Humanos; Glioma/diagnóstico por imagem; Neoplasias Encefálicas/diagnóstico por imagem; Peso Corporal; Encéfalo; Processamento de Imagem Assistida por Computador

Palavras-chave

MRI; attention mechanism; brain glioma; convolutional neural network (CNN); optimal fusion

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Guideline / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

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