MRI Gibbs-ringing artifact reduction by means of machine learning using convolutional neural networks.

Abstract

Authors

• Qianqian Zhang
  Department of Civil Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L7 E-mail: zoeli@mcmaster.ca; School of Management, Chengdu University of Information Technology, Chengdu 610225, China.
• Guohui Ruan
  School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
• Wei Yang
  Key Laboratory of Structure-Based Drug Design and Discovery (Shenyang Pharmaceutical University), Ministry of Education, School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Wenhua Road 103, Shenyang 110016, PR China. Electronic address: 421063202@qq.com.
• Yilong Liu
  Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China.
• Kaixuan Zhao
  School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
• Qianjin Feng
  Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China. Electronic address: qianjinfeng08@gmail.com.
• Wufan Chen
  Guangdong Provincial Key Laboratory of Medical Image Processing, School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
• Ed X Wu
  Laboratory of Biomedical Imaging and Signal Processing, The University of Hong Kong, Hong Kong SAR, China.
• Yanqiu Feng
  School of Biomedical Engineering, Southern Medical University, Guangzhou, China.

Keywords

External Resources