Comparison of conventional diffusion-weighted imaging and multiplexed sensitivity-encoding combined with deep learning-based reconstruction in breast magnetic resonance imaging.

Abstract

Authors

• Yitian Xiao
  Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
• Fan Yang
  School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou, China.
• Qiao Deng
  Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
• Yue Ming
  Beijing Key Laboratory of Work Safety and Intelligent Monitoring, School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing, China.
• Lu Tang
  Department of Communication and Journalism, Texas A&M University.
• Shuting Yue
  Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
• Zheng Li
  Department of Integrated Pulmonology, Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.
• Bo Zhang
  Department of Clinical Pharmacology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310006, PR China.
• Huilou Liang
  GE HealthCare MR Research, Beijing, China.
• Juan Huang
  State Key Laboratory of Medicinal Chemical Biology, Tianjin Key Laboratory of Biosensing and Molecular Recognition, Nankai University, Tianjin 300071, PR China.
• Jiayu Sun
  Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, China.

Keywords

External Resources