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Artificial intelligence in image-guided radiotherapy: A review of treatment target localization

  • Wei Zhao*
  • , Liyue Shen
  • , Md Tauhidul Islam
  • , Wenjian Qin
  • , Zhicheng Zhang
  • , Xiaokun Liang
  • , Gaolong Zhang
  • , Shouping Xu
  • , Xiaomeng Li*
  • *此作品的通讯作者
  • Stanford University
  • Shenzhen Institute of Advanced Technology
  • General Hospital of People's Liberation Army
  • Hong Kong University of Science and Technology

科研成果: 期刊稿件文献综述同行评审

摘要

Modern conformal beam delivery techniques require image-guidance to ensure the prescribed dose to be delivered as planned. Recent advances in artificial intelligence (AI) have greatly augmented our ability to accurately localize the treatment target while sparing the normal tissues. In this paper, we review the applications of AI-based algorithms in image-guided radiotherapy (IGRT), and discuss the indications of these applications to the future of clinical practice of radiotherapy. The benefits, limitations and some important trends in research and development of the AI-based IGRT techniques are also discussed. AI-based IGRT techniques have the potential to monitor tumor motion, reduce treatment uncertainty and improve treatment precision. Particularly, these techniques also allow more healthy tissue to be spared while keeping tumor coverage the same or even better.

源语言英语
页(从-至)4881-4894
页数14
期刊Quantitative Imaging in Medicine and Surgery
11
12
DOI
出版状态已出版 - 12月 2021

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