Lung volume reduction and infection localization revealed in Big data CT imaging of COVID-19

Feng Shi, Ying Wei, Liming Xia, Fei Shan, Zhanhao Mo, Fuhua Yan, Dinggang Shen

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

The ongoing worldwide COVID-19 pandemic has become a huge threat to global public health. Using CT image, 3389 COVID-19 patients, 1593 community-acquired pneumonia (CAP) patients, and 1707 nonpneumonia subjects were included to explore the different patterns of lung and lung infection. We found that COVID-19 patients have a significant reduced lung volume with increased density and mass, and the infections tend to present as bilateral lower lobes. The findings provide imaging evidence to improve our understanding of COVID-19.

Original languageEnglish
Pages (from-to)316-318
Number of pages3
JournalInternational Journal of Infectious Diseases
Volume102
DOIs
Publication statusPublished - 2021 Jan

Keywords

  • Big data
  • COVID-19
  • Community-Acquired pneumonia
  • Lung
  • Non-Pneumonia subjects

ASJC Scopus subject areas

  • Microbiology (medical)
  • Infectious Diseases

Fingerprint

Dive into the research topics of 'Lung volume reduction and infection localization revealed in Big data CT imaging of COVID-19'. Together they form a unique fingerprint.

Cite this