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.

Afiliación

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 en En | MEDLINE | ID: mdl-35935468

Palabras clave

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

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Signal Process Image Commun Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos

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