Cargando…
Deep learning-based multi-view fusion model for screening 2019 novel coronavirus pneumonia: A multicentre study
PURPOSE: To develop a deep learning-based method to assist radiologists to fast and accurately identify patients with COVID-19 by CT images. METHODS: We retrospectively collected chest CT images of 495 patients from three hospitals in China. 495 datasets were randomly divided into 395 cases (80%, 29...
Autores principales: | Wu, Xiangjun, Hui, Hui, Niu, Meng, Li, Liang, Wang, Li, He, Bingxi, Yang, Xin, Li, Li, Li, Hongjun, Tian, Jie, Zha, Yunfei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier B.V.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198437/ https://www.ncbi.nlm.nih.gov/pubmed/32408222 http://dx.doi.org/10.1016/j.ejrad.2020.109041 |
Ejemplares similares
-
CT radiomics can help screen the Coronavirus disease 2019 (COVID-19): a preliminary study
por: Fang, Mengjie, et al.
Publicado: (2020) -
A Deep Learning System to Screen Novel Coronavirus Disease 2019 Pneumonia
por: Xu, Xiaowei, et al.
Publicado: (2020) -
New thinking in the treatment of 2019 novel coronavirus pneumonia
por: Yang, Qing-Xin, et al.
Publicado: (2020) -
Two-stage hybrid network for segmentation of COVID-19 pneumonia lesions in CT images: a multicenter study
por: Shang, Yaxin, et al.
Publicado: (2022) -
RETRACTED ARTICLE: Deep learning system to screen coronavirus disease 2019 pneumonia
por: Butt, Charmaine, et al.
Publicado: (2020)