Unsupervised deep learning model for correcting Nyquist ghosts of single-shot spatiotemporal encoding.

Abstract

Authors

• Qingjia Bao
  Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, China.
• Xinjie Liu
  Guangzhou Inspection and Testing Certification Group Company Limited, National Quality Testing Center for Processed Food, Guangzhou 511447, China.
• Jingyun Xu
  Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education,; School of Software Engineering, South China University of Technology, Guangzhou, China.
• Liyang Xia
  School of Information Engineering, Wuhan University of Technology, Wuhan, China.
• Martins Otikovs
  Weizmann Institute of Science, Rehovot, Israel.
• Han Xie
  Key Laboratory of Magnetic Resonance in Biological Systems, Innovation Academy for Precision Measurement Science and Technology, Wuhan, China.
• Kewen Liu
  School of Information Engineering, Wuhan University of Technology, Wuhan, China.
• Zhi Zhang
  National Engineering Research Center for Beijing Biochip Technology, Beijing, China.
• Xin Zhou
  School of Mechatronic Engineering, China University of Mining & Technology, Xuzhou 221116, China.
• Chaoyang Liu
  Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of Sciences-Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China.

Keywords

External Resources