Journal of International Oncology ›› 2022, Vol. 49 ›› Issue (3): 168-172.doi: 10.3760/cma.j.cn371439-20220104-00028

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Application of artificial intelligence in the target delineation of radiotherapy

Yan Danfang1, Wang Lihong1, Ye Hongxing2, Yan Senxiang1()   

  1. 1Department of Radiation Oncology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
    2Department of Neurosurgery, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China
  • Received:2022-01-04 Revised:2022-02-13 Online:2022-03-08 Published:2022-03-22
  • Contact: Yan Senxiang E-mail:yansenxiang@zju.edu.cn
  • Supported by:
    Natural Science Foundation of Zhejiang Province of China(LSY19H160004);Natural Science Foundation of Zhejiang Province of China(LY18H160020);National Key Research and Development Project of Scientific and Technological Innovation 2030—“New Generation Artificial Intelligence” Major Project(2018AAA0102102)

Abstract:

Artificial intelligence is the use of computer algorithms to copy or simulate human behavior, giving machines human-like ability. With the rapid development of radiotherapy technology, artificial intelligence has great potential value in all stages of radiotherapy. Image segmentation is the premise of target delineation using artificial intelligence. The commonly used methods in clinic mainly include automatic segmentation based on deep learning and atlas library. The technology of artificial intelligence in organs at risk delineation is relatively mature, which can significantly shorten the delineation time and improve the efficiency. The delineation of tumor targets has achieved some success, the accuracy still needs to be further improved. Artificial intelligence technology makes the target delineation more and more efficient, and the consistency and repeatability have been significantly improved. It is expected to provide more accurate and individualized treatment for patients.

Key words: Radiotherapy, Artificial intelligence, Image segmentation, Target delineation