SSA-Net: Spatial self-attention network for COVID-19 pneumonia infection segmentation with semi-supervised few-shot learning

Coronavirus disease (COVID-19) broke out at the end of 2019, and has resulted in an ongoing global pandemic. Segmentation of pneumonia infections from chest computed tomography (CT) scans of COVID-19 patients is significant for accurate diagnosis and quantitative analysis. Deep learning-based method...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Xiaoyan, Yuan, Yiwen, Guo, Dongyan, Huang, Xiaojie, Cui, Ying, Xia, Ming, Wang, Zhenhua, Bai, Cong, Chen, Shengyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier B.V. 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9027296/
https://www.ncbi.nlm.nih.gov/pubmed/35544999
http://dx.doi.org/10.1016/j.media.2022.102459

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9027296/
https://www.ncbi.nlm.nih.gov/pubmed/35544999
http://dx.doi.org/10.1016/j.media.2022.102459

Ejemplares similares