国际肿瘤学杂志 ›› 2022, Vol. 49 ›› Issue (3): 168-172.doi: 10.3760/cma.j.cn371439-20220104-00028

• 综述 • 上一篇    下一篇

人工智能在肿瘤放疗靶区勾画中的应用

严丹方1, 王立宏1, 叶红星2, 严森祥1()   

  1. 1浙江大学医学院附属第一医院放疗科,杭州 310003
    2浙江大学医学院附属第一医院神经外科,杭州 310003
  • 收稿日期:2022-01-04 修回日期:2022-02-13 出版日期:2022-03-08 发布日期:2022-03-22
  • 通讯作者: 严森祥 E-mail:yansenxiang@zju.edu.cn
  • 基金资助:
    浙江省自然科学基金(LSY19H160004);浙江省自然科学基金(LY18H160020);国家重点研发项目科技创新2030—“新一代人工智能”重大项目(2018AAA0102102)

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)

摘要:

人工智能是一种使用计算机算法来复制或模拟人类的行为,使机器拥有和人类相似的能力。随着放疗技术的飞速发展,人工智能在放疗的各个阶段均有巨大应用价值。图像分割是人工智能靶区勾画的前提,常用的应用于临床的方法主要包括基于深度学习和基于图谱库的自动分割方法。人工智能勾画危及器官技术较成熟,可显著缩短勾画时间,提高效率;勾画肿瘤靶区初有成就,在精确性方面仍有待进一步提高。人工智能技术使放疗靶区勾画越来越高效,一致性、重复性均得到了明显提升,有望为肿瘤患者提供更加精准及个体化的治疗方案。

关键词: 放射疗法, 人工智能, 图像分割, 靶区勾画

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