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

Haonan Xiao, Ge Ren, Jing Cai

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

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
Volume1
Issue number4
DOIs
Publication statusPublished - Dec 2020

Keywords

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

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