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Deep learning-based medical image registration

  • Xiaohuan Cao
  • , Peng Xue
  • , Jingfan Fan
  • , Dingkun Liu
  • , Kaicong Sun
  • , Zhong Xue
  • , Dinggang Shen
  • Shanghai United Imaging Healthcare Co., Ltd.
  • ShanghaiTech University
  • Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Medical image registration aims to establish anatomical correspondences between images of different subjects or the same subject acquired at different time points or between images of different imaging modalities. It is a critical technique used in many clinical applications, such as population analysis, longitudinal studies, multi-modal image fusion and image-guided intervention. In recent years, deep learning, especially deep convolutional neural networks (CNNs), has shown great success in medical image registration. In this chapter, we introduce the recent development of deep learning-based medical image registration methods. Conventional and machine learning-based registration methods will also be introduced briefly.

Original languageEnglish
Title of host publicationDeep Learning for Medical Image Analysis
PublisherElsevier
Pages337-356
Number of pages20
ISBN (Electronic)9780323851244
ISBN (Print)9780323858885
DOIs
Publication statusPublished - 1 Jan 2023
Externally publishedYes

Keywords

  • Deep learning-based registration
  • Medical image registration
  • Semantic registration

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