MID-UNet: Multi-input directional UNet for COVID-19 lung infection segmentation from CT images.

Chi, Jianning; Zhang, Shuang; Han, Xiaoying; Wang, Huan; Wu, Chengdong; Yu, Xiaosheng

Chi, Jianning; Zhang, Shuang; Han, Xiaoying; Wang, Huan; Wu, Chengdong; Yu, Xiaosheng.

Afiliação

Chi J; Northeastern University, NO. 195, Chuangxin Road, Hunnan District, Shenyang, China.
Zhang S; Northeastern University, NO. 195, Chuangxin Road, Hunnan District, Shenyang, China.
Han X; Northeastern University, NO. 195, Chuangxin Road, Hunnan District, Shenyang, China.
Wang H; Northeastern University, NO. 195, Chuangxin Road, Hunnan District, Shenyang, China.
Wu C; Northeastern University, NO. 195, Chuangxin Road, Hunnan District, Shenyang, China.
Yu X; Northeastern University, NO. 195, Chuangxin Road, Hunnan District, Shenyang, China.

Signal Process Image Commun ; 108: 116835, 2022 Oct.

Article em En | MEDLINE | ID: mdl-35935468

Palavras-chave

COVID-19; CT image; Convolutional neural networks; Deep learning; Infection segmentation

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Signal Process Image Commun Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Holanda

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