Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89687
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Title: A review on 3D deformable image registration and its application in dose warping
Authors: Xiao, H 
Ren, G 
Cai, J 
Issue Date: Dec-2020
Source: Radiation medicine and protection , Dec. 2020, v. 1, no. 4, p. 171-178
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.
Keywords: Deformable image registration (DIR)
Deep learning
Dose summation
Dose accumulation
Publisher: Ke Ai Publishing Communications Ltd.
Journal: Radiation medicine and protection 
EISSN: 2666-5557
DOI: 10.1016/j.radmp.2020.11.002
Rights: © 2020 National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention. Production and hosting by Elsevier B.V. on behalf of KeAi. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The following publication Xiao, H., Ren, G., & Cai, J. (2020). A review on 3D deformable image registration and its application in dose warping. Radiation Medicine and Protection, 1(4), 171-178 is available at https://doi.org/10.1016/j.radmp.2020.11.002.
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