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METHODS AND SYSTEMS FOR RADIOTHERAPY TREATMENT PLANNING USING DEEP LEARNING ENGINES

机译:使用深度学习引擎进行放射治疗计划的方法和系统

摘要

Example methods for radiotherapy treatment planning using deep learning engines are provided. One example method may comprise obtaining first image data associated with a patient; generating first feature data by processing the first image data associated with a first resolution level using a first processing pathway; generating second feature data by processing second image data associated with a second resolution level using a second processing pathway; and generating third feature data by processing third image data associated with a third resolution level using a third processing pathway. The example method may also comprise generating a first combined set of feature data associated with the second resolution level, and a second combined set of feature data associated with the first resolution level based on the first feature data and the first combined set. Further, the example method may comprise generating output data associated with radiotherapy treatment of the patient.
机译:提供了使用深度学习引擎进行放射疗法治疗计划的示例方法。一个示例方法可以包括获得与患者相关联的第一图像数据;通过使用第一处理路径处理与第一分辨率等级相关联的第一图像数据来生成第一特征数据;通过使用第二处理路径处理与第二分辨率等级相关联的第二图像数据来生成第二特征数据;通过使用第三处理路径处理与第三分辨率等级相关联的第三图像数据来生成第三特征数据。该示例方法还可以包括基于第一特征数据和第一组合集,生成与第二分辨率等级相关联的特征数据的第一组合集合,以及与第一分辨率等级相关联的特征数据的第二组合集合。此外,该示例方法可以包括生成与患者的放射疗法治疗相关的输出数据。

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