Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning.

Journal: European radiology
Published Date: Jun 1, 2020

Abstract

OBJECTIVES: To take advantage of the deep learning algorithms to detect and calculate clot burden of acute pulmonary embolism (APE) on computed tomographic pulmonary angiography (CTPA).

Authors

  • Weifang Liu
    Peking University Health Science Center, Beijing, 100871, China.
  • Min Liu
    Department of Critical Care Medicine, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi People's Hospital, Wuxi Medical Center, Nanjing Medical University, Wuxi, China.
  • Xiaojuan Guo
    College of Information Science and Technology, Beijing Normal University, Beijing, China.
  • Peiyao Zhang
    Department of Radiology, China-Japan Friendship Hospital, 2 Yinghua Dong Street, Hepingli, Chao Yang District, Beijing, 100029, China.
  • Ling Zhang
  • Rongguo Zhang
    Infervision, Beijing, China.
  • Han Kang
    Artificial Intelligence Scholar Center, Infervision, Beijing, 100025, China.
  • Zhenguo Zhai
    Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, 100029, China.
  • Xincao Tao
    Department of Pulmonary and Critical Care Medicine, China-Japan Friendship Hospital, Beijing, 100029, China.
  • Jun Wan
    Department of Medical and Molecular Genetics, Collaborative Core for Cancer Bioinformatics, Indianapolis, IN.
  • Sheng Xie
    Department of Radiology, China-Japan Friendship Hospital, 2 Yinghua Dong Street, Hepingli, Chao Yang District, Beijing, 100029, China. xs_mri@126.com.

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