UDRSNet: An unsupervised deformable registration module based on image structure similarity.

Journal: Medical physics
Published Date: Feb 14, 2024

Abstract

BACKGROUND: Image registration is a challenging problem in many clinical tasks, but deep learning has made significant progress in this area over the past few years. Real-time and robust registration has been made possible by supervised transformation estimation. However, the quality of registrations using this framework depends on the quality of ground truth labels such as displacement field.

Authors

  • Yun Wang
    Department of Anesthesiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100050, People's Republic of China.
  • Chongfei Huang
    The School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China.
  • Wanru Chang
    School of Mathematical Sciences, Zhejiang University, Hangzhou, China.
  • Wenliang Lu
    School of Mathematical Sciences, Zhejiang University, Hangzhou, China.
  • Qinglei Hui
    School of Mathematics and Statistics, Anyang Normal University, Anyang, China.
  • Siyuan Jiang
    Zhejiang Demetics Medical Technology Co., Ltd, Hangzhou, China.
  • Xiaoping Ouyang
    College of Business Administration, Hunan University Changsha 410082, PR China.
  • Dexing Kong
    School of Mathematical Sciences, Zhejiang University, Hangzhou 310027, China. Electronic address: dkong@zju.edu.cn.

Keywords

External Resources

Popular Topics
Recent Journals