From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans

Zhang Li; Zheng Zhong; Yang Li; Tianyu Zhang; Liangxin Gao; Dakai Jin; Yue Sun; Xianghua Ye; Li Yu; Zheyu Hu; Jing Xiao; Lingyun Huang; Yuling Tang

doi:10.1007/s00330-020-07042-x

From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans

Zhang Li, Zheng Zhong, Yang Li, Tianyu Zhang, Liangxin Gao, Dakai Jin, Yue Sun, Xianghua Ye, Li Yu, Zheyu Hu, Jing Xiao, Lingyun Huang^*, Yuling Tang^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Original language	English
Pages (from-to)	6828-6837
Number of pages	10
Journal	European Radiology
Volume	30
Issue number	12
Early online date	18 Jul 2020
DOIs	https://doi.org/10.1007/s00330-020-07042-x
Publication status	Published - Dec 2020

Keywords

COVID-19
Deep learning
Disease progression
Artificial intelligence

Access to Document

10.1007/s00330-020-07042-x

Cite this

Li, Zhang ; Zhong, Zheng ; Li, Yang ; Zhang, Tianyu ; Gao, Liangxin ; Jin, Dakai ; Sun, Yue ; Ye, Xianghua ; Yu, Li ; Hu, Zheyu ; Xiao, Jing ; Huang, Lingyun ; Tang, Yuling. / From community-acquired pneumonia to COVID-19 : a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans. In: European Radiology. 2020 ; Vol. 30, No. 12. pp. 6828-6837.

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title = "From community-acquired pneumonia to COVID-19: a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans",

keywords = "COVID-19, Deep learning, Disease progression, Artificial intelligence",

author = "Zhang Li and Zheng Zhong and Yang Li and Tianyu Zhang and Liangxin Gao and Dakai Jin and Yue Sun and Xianghua Ye and Li Yu and Zheyu Hu and Jing Xiao and Lingyun Huang and Yuling Tang",

year = "2020",

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language = "English",

volume = "30",

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From community-acquired pneumonia to COVID-19 : a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans. / Li, Zhang; Zhong, Zheng; Li, Yang; Zhang, Tianyu; Gao, Liangxin; Jin, Dakai; Sun, Yue; Ye, Xianghua; Yu, Li; Hu, Zheyu; Xiao, Jing; Huang, Lingyun; Tang, Yuling.

In: European Radiology, Vol. 30, No. 12, 12.2020, p. 6828-6837.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - From community-acquired pneumonia to COVID-19

T2 - a deep learning-based method for quantitative analysis of COVID-19 on thick-section CT scans

AU - Li, Zhang

AU - Zhong, Zheng

AU - Li, Yang

AU - Zhang, Tianyu

AU - Gao, Liangxin

AU - Jin, Dakai

AU - Sun, Yue

AU - Ye, Xianghua

AU - Yu, Li

AU - Hu, Zheyu

AU - Xiao, Jing

AU - Huang, Lingyun

AU - Tang, Yuling

PY - 2020/12

Y1 - 2020/12

KW - COVID-19

KW - Deep learning

KW - Disease progression

KW - Artificial intelligence

U2 - 10.1007/s00330-020-07042-x

DO - 10.1007/s00330-020-07042-x

M3 - Article

C2 - 32683550

VL - 30

SP - 6828

EP - 6837

JO - European Radiology

JF - European Radiology

SN - 0938-7994

IS - 12

ER -