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    • 8. 发明授权
    • Automatic generation of patient-specific radiation therapy planning parameters
    • 自动生成患者特异性放射治疗计划参数
    • US08976929B2
    • 2015-03-10
    • US13184746
    • 2011-07-18
    • Qingrong Jackie WuYaorong GeFang-Fang YinXiaofeng Zhu
    • Qingrong Jackie WuYaorong GeFang-Fang YinXiaofeng Zhu
    • A61N5/10H05G1/26A61B6/03
    • A61N5/10A61N5/1031A61N2005/1041
    • An apparatus and method for automatically generating radiation treatment planning parameters are disclosed. In accordance with the illustrative embodiment, a database is constructed that stores: (i) patient data and past treatment plans by expert human planners for these patients, and (ii) optimal treatment plans that are generated using multi-objective optimization and Pareto front search and that represent the best tradeoff opportunities of the patient case, and a predictive model (e.g., a neural network, a decision tree, a support vector machine [SVM], etc.) is then trained via a learning algorithm on a plurality of input/output mappings derived from the contents of the database. During training, the predictive model is trained to identify and infer patterns in the treatment plan data through a process of generalization. Once trained, the predictive model can then be used to automatically generate radiation treatment planning parameters for new patients.
    • 公开了一种用于自动产生辐射治疗计划参数的装置和方法。 根据说明性实施例,构建数据库,其存储:(i)专家人类计划者对这些患者的患者数据和过去的治疗计划,以及(ii)使用多目标优化和帕累托前向搜索生成的最佳治疗计划 并且代表患者情况的最佳权衡机会,然后通过多个输入上的学习算法来训练预测模型(例如,神经网络,决策树,支持向量机[SVM]等) /输出从数据库内容导出的映射。 在训练期间,通过一般化过程对预测模型进行训练,以便识别和推断治疗计划数据中的模式。 经过训练后,可以使用预测模型自动生成新患者的放射治疗计划参数。
    • 10. 发明申请
    • Automatic Generation of Patient-Specific Radiation Therapy Planning Parameters
    • 自动生成患者特异性放射治疗计划参数
    • US20120014507A1
    • 2012-01-19
    • US13184746
    • 2011-07-18
    • Qingrong Jackie WuYaorong GeFang-Fang YinXiaofeng Zhu
    • Qingrong Jackie WuYaorong GeFang-Fang YinXiaofeng Zhu
    • A61N5/10
    • A61N5/10A61N5/1031A61N2005/1041
    • An apparatus and method for automatically generating radiation treatment planning parameters are disclosed. In accordance with the illustrative embodiment, a database is constructed that stores: (i) patient data and past treatment plans by expert human planners for these patients, and (ii) optimal treatment plans that are generated using multi-objective optimization and Pareto front search and that represent the best tradeoff opportunities of the patient case, and a predictive model (e.g., a neural network, a decision tree, a support vector machine [SVM], etc.) is then trained via a learning algorithm on a plurality of input/output mappings derived from the contents of the database. During training, the predictive model is trained to identify and infer patterns in the treatment plan data through a process of generalization. Once trained, the predictive model can then be used to automatically generate radiation treatment planning parameters for new patients.
    • 公开了一种用于自动产生辐射治疗计划参数的装置和方法。 根据说明性实施例,构建数据库,其存储:(i)专家人类计划者对这些患者的患者数据和过去的治疗计划,以及(ii)使用多目标优化和帕累托前向搜索生成的最佳治疗计划 并且代表患者情况的最佳权衡机会,然后通过多个输入上的学习算法来训练预测模型(例如,神经网络,决策树,支持向量机[SVM]等) /输出从数据库内容导出的映射。 在训练期间,通过一般化过程对预测模型进行训练,以便识别和推断治疗计划数据中的模式。 经过训练后,可以使用预测模型自动生成新患者的放射治疗计划参数。