When investigating new radiation therapy techniques in the treatment planning stage, it can be extremely time consuming to locate multiple patient scans that match the desired characteristics for the treatment. With the help of machine learning, we propose to bypass the difficulty in finding patient computed tomography (CT) scans that match the treatment requirements. Furthermore, we aim to provide the developed method as a tool that is easily accessible to interested researchers.

中文翻译：

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技术说明：在计算机断层扫描图像中合成肺部肿瘤。

在治疗计划阶段研究新的放射治疗技术时，定位与治疗所需特征匹配的多个患者扫描可能非常耗时。在机器学习的帮助下，我们建议绕过寻找符合治疗要求的患者计算机断层扫描（CT）扫描的难题。此外，我们旨在提供一种开发的方法，作为感兴趣的研究人员可以轻松使用的工具。