论文标题
自动化的WBRT治疗计划通过深度学习自动包装和可自定义的基于里程碑的现场光圈设计
Automated WBRT Treatment Planning via Deep Learning Auto-Contouring and Customizable Landmark-Based Field Aperture Design
论文作者
论文摘要
在这项工作中，我们开发并评估了一条新的管道，该管道包括两种基于具有里程碑意义的现场孔径生成方法，用于WBRT治疗计划；它们是完全自动化的，可自定义。自动化管道对临床医生和患者都是有益的，我们可以减少临床医生的工作量并减少治疗计划时间。场孔设计的可定制性解决了不同的临床要求，并允许个性化设计变得可行。关于定量和定性评估的绩效结果表明，我们的计划与最初的临床计划相媲美。该技术已被部署为全脑癌的全自动治疗计划工具的一部分，将来可以转化为其他治疗部位。
In this work, we developed and evaluated a novel pipeline consisting of two landmark-based field aperture generation approaches for WBRT treatment planning; they are fully automated and customizable. The automation pipeline is beneficial for both clinicians and patients, where we can reduce clinician workload and reduce treatment planning time. The customizability of the field aperture design addresses different clinical requirements and allows the personalized design to become feasible. The performance results regarding quantitative and qualitative evaluations demonstrated that our plans were comparable with the original clinical plans. This technique has been deployed as part of a fully automated treatment planning tool for whole-brain cancer and could be translated to other treatment sites in the future.
