Despite being the standard metric in patient‐specific quality assurance (QA) for intensity‐modulated radiotherapy (IMRT), gamma analysis has two shortcomings: (a) it lacks sensitivity to small but clinically relevant errors (b) it does not provide efficient means to classify the error sources. The purpose of this work is to propose a dual neural network method to achieve simultaneous error detection and classification in patient‐specific IMRT QA.

中文翻译：

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具有双神经网络的患者特定IMRT QA中的错误检测和分类

尽管伽玛分析是强度调制放射疗法（IMRT）的患者特定质量保证（QA）的标准指标，但它有两个缺点：（a）对微小但与临床相关的错误缺乏敏感性（b）无法提供有效的手段对错误源进行分类。这项工作的目的是提出一种双重神经网络方法，以实现针对患者的IMRT QA的同时错误检测和分类。