COVID-19 CT ground-glass opacity segmentation based on attention mechanism threshold.

Rao, Yunbo; Lv, Qingsong; Zeng, Shaoning; Yi, Yuling; Huang, Cheng; Gao, Yun; Cheng, Zhanglin; Sun, Jihong

Rao, Yunbo; Lv, Qingsong; Zeng, Shaoning; Yi, Yuling; Huang, Cheng; Gao, Yun; Cheng, Zhanglin; Sun, Jihong.

Affiliation

Rao Y; School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Lv Q; School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Zeng S; Yangtze Delta Region Institute (Huzhou), University of Electronic Science and Technology of China, Huzhou, 313000, China.
Yi Y; School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China.
Huang C; Fifth Clinical College of Chongqing Medical University, Chongqing, 402177, China.
Gao Y; Chongqing University of Posts and Telecommunications, Chongqing, 400065, China.
Cheng Z; Advanced Technology Chinese Academy of Sciences, Shenzhen, 610042, China.
Sun J; Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, 310014, China.

Biomed Signal Process Control ; 81: 104486, 2023 Mar.

Article de En | MEDLINE | ID: mdl-36505089

Mots clés

Adaptive threshold; Attention mechanism; COVID-19; CT image; GGO segmentation; Pneumonia

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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Langue: En Journal: Biomed Signal Process Control Année: 2023 Type de document: Article Pays d'affiliation: Chine Pays de publication: Royaume-Uni

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