Super-resolution reconstruction of knee magnetic resonance imaging based on deep learning.

Journal: Computer methods and programs in biomedicine
Published Date: Sep 24, 2019

Abstract

BACKGROUND AND OBJECTIVE: With the rapid development of medical imaging and intelligent diagnosis, artificial intelligence methods have become a research hotspot of radiography processing technology in recent years. The low definition of knee magnetic resonance image texture seriously affects the diagnosis of knee osteoarthritis. This paper presents a super-resolution reconstruction method to address this problem.

Authors

  • Defu Qiu
    Engineering Research Centre in Industrial Intellectual Techniques and Systems of Fujian Providence College of Engineering, Huaqiao University, Chenghua North Road, Fengze District, Quanzhou, Fujian 362021, China. Electronic address: 17014084010@hqu.edu.cn.
  • Shengxiang Zhang
    Engineering Research Centre in Industrial Intellectual Techniques and Systems of Fujian Providence College of Engineering, Huaqiao University, Chenghua North Road, Fengze District, Quanzhou, Fujian 362021, China. Electronic address: 1611422010@hqu.edu.cn.
  • Ying Liu
    The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
  • Jianqing Zhu
    Engineering Research Centre in Industrial Intellectual Techniques and Systems of Fujian Providence College of Engineering, Huaqiao University, Chenghua North Road, Fengze District, Quanzhou, Fujian 362021, China. Electronic address: jqzhu@hqu.edu.cn.
  • Lixin Zheng
    Engineering Research Centre in Industrial Intellectual Techniques and Systems of Fujian Providence College of Engineering, Huaqiao University, Chenghua North Road, Fengze District, Quanzhou, Fujian 362021, China. Electronic address: zlx@hqu.edu.cn.

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