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  • eess.IV1
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most citedFederated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

11 citations

researchers with a paper here
  • Andriy Myronenko1 · h 26
  • Bradford J. Wood1 · h 3
  • B. Turkbey1 · h 90
  • Daguang Xu1 · h 4
  • Dong Yang1 · h 6
  • E. Turkbey1 · h 36
  • F. Patella1 · h 17
  • G. Carrafiello1 · h 8
  • Hitoshi Mori1 · h 9
  • H. Obinata1 · h 12
  • Holger Roth1 · h 3
  • Kaku Tamura1 · h 14
collaborating institutions
  • Center for Cancer ResearchUS1 paper
  • Fondazione IRCCS Ca' Granda Ospedale Maggiore PoliclinicoIT1 paper
  • Hubei University of MedicineCN1 paper
  • National Cancer InstituteUS1 paper
  • National Institutes of Health Clinical CenterUS1 paper
  • Nvidia (United States)US1 paper
  • Self-Defense Forces Central HospitalJP1 paper
  • Xiang Yang No.1 People's HospitalCN1 paper

1 paper

eess.IV2020★ 11 cited

Federated Semi-Supervised Learning for COVID Region Segmentation in Chest CT using Multi-National Data from China, Italy, Japan

Dong Yang, Ziyue Xu, Wenqi Li +17

The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able t…

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