Synthetic CT generation for pelvic cases based on deep learning in multi-center datasets.

Abstract

Authors

• Xianan Li
  Institute of Medical Intelligence, Department of Artificial Intelligence, Beijing Key Lab of Traffic Data Analysis and Mining, School of Computer Science & Technology, Beijing Jiaotong University, Beijing 100044, China.
• Lecheng Jia
  Shenzhen United Imaging Research Institute of Innovative Medical Equipment, Shenzhen, China. lecheng.jia@cri-united-imaging.com.
• Fengyu Lin
  YIWEI Medical Technology Co., Ltd, Room 1001, MAI KE LONG Building, Nanshan, ShenZhen, 518000, China.
• Fan Chai
  Department of Radiology, Peking University People's Hospital, Beijing, 100044, China.
• Tao Liu
  Institute of Urology and Nephrology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
• Wei Zhang
  The First Affiliated Hospital of Nanchang University, Nanchang, China.
• Ziquan Wei
  Collaborative Innovation Center for Biomedical Engineering, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan, Hubei, China.
• Weiqi Xiong
  Shanghai United Imaging Healthcare Co., Ltd. Shanghai, Shanghai, China.
• Hua Li
  Department of Stomatology, The First Medical Center Chinese PLA General Hospital Beijing China.
• Min Zhang
  Department of Infectious Disease, The Second Xiangya Hospital of Central South University, Changsha, China.
• Yi Wang
  Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.

Keywords

External Resources