A review on 3D deformable image registration and its application in dose warping

Haonan Xiao, Ge Ren, Jing Cai

Research output: Journal article publicationReview articleAcademic researchpeer-review

11 Citations (Scopus)


Deformable image registration (DIR) has been well explored in recent decades, and it is widely utilized in clinical tasks, especially dose warping. Nowadays, as deep learning (DL) develops rapidly, many DL-based methods were also applied in DIR. This paper reviews DL-based DIR methods in recent years and the application of DIR in dose warping. We collected and categorized the latest DL-based DIR studies. A thorough review of each category was presented, in which studies were discussed based on their supervision, advantage, and challenges. Then, we reviewed DIR-based dose warping and discussed its rationale, feasibility, successes, and difficulties. Lastly, we summarized the review on both parts and discussed their future development trend.

Original languageEnglish
Pages (from-to)171-178
Number of pages8
JournalRadiation Medicine and Protection
Issue number4
Publication statusPublished - Dec 2020


  • Deep learning
  • Deformable image registration (DIR)
  • Dose accumulation
  • Dose summation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Public Health, Environmental and Occupational Health
  • Emergency Medical Services
  • Radiological and Ultrasound Technology


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