Machine learning-based hemodynamics quantitative assessment of pulmonary circulation using computed tomographic pulmonary angiography.

Abstract

Authors

• Hongyan Xie
  Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Rd, Chaoyang District, Beijing, China.
• Xin Zhao
  Florida International University.
• Nan Zhang
  Department of Pulmonary and Critical Care Medicine II, Emergency General Hospital, Beijing, China.
• Jiayi Liu
  Beijing University of Chinese Medicine, China-Japan Friendship Clinical School of Medicine, Beijing, 100029, People's Republic of China.
• Guang Yang
  National Heart and Lung Institute, Imperial College London, London, UK.
• Yunshan Cao
  Department of Cardiology, Gansu Provincial Hospital, Lanzhou, Gansu, China; Heart, Lung and Vessels Center, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
• Jialin Xu
  E204, Wu Yee Sun college, Chinese University of Hong Kong, Shatin, NT, HK.
• Lei Xu
  Key Laboratory of Biomedical Information Engineering of the Ministry of Education, Department of Biomedical Engineering, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
• Zhonghua Sun
  Beijing Univ. of Technology, China.
• Zhaoying Wen
  Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Rd, Chaoyang District, Beijing, China.
• Senchun Chai
  Department of Automation, School of automation, Beijing Institute of Technology, People's Republic of China.
• Dongting Liu
  Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, No. 2 Anzhen Rd, Chaoyang District, Beijing, China. Electronic address: dongting0530@163.com.

Keywords

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