Online dose verification based on proton‐induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between dose and the activity distributions, a machine learning‐based approach was developed to establish their relationship.

中文翻译：

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利用正电子发射断层扫描（PET）和生成对抗网络（GAN）在质子治疗中验证患者特定剂量的可行性研究。

基于质子诱导的正电子发射体的在线剂量验证是一种有前景的质子治疗质量保证策略。由于剂量和活性分布之间存在非线性关系，因此开发了一种基于机器学习的方法来建立它们之间的关系。