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相关概念视频

Radiation Pressure: Problem Solving01:09

Radiation Pressure: Problem Solving

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The radiation pressure applied by an electromagnetic wave on a perfectly absorbing surface equals the energy density of the wave. The wave's momentum also gets transferred to the surface when an electromagnetic wave is entirely absorbed by it. The rate at which momentum is transmitted to an absorbing surface perpendicular to the propagation direction equals the force on the surface.
The average value of the rate of momentum transfer divided by the absorbing area represents the average force...
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Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
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相关实验视频

Updated: Jul 17, 2025

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
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一个统一的路径搜索算法,用于IMRT和IMPT光束方向优化.

Pavitra Ramesh1, Gilmer Valdes2, Daniel O'Connor3

  • 1Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA 90095, United States of America.

Physics in medicine and biology
|September 2, 2023
PubMed
概括
此摘要是机器生成的。

一个新的自动化算法,PathGD,改善了强度调节放射治疗和质子治疗的光束方向优化. 它有效地选择光束,提高图形质量并减少对健康组织的辐射剂量.

关键词:
光束的选择和选择.剂量优化剂量优化路径搜索算法 路径搜索算法

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相关实验视频

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科学领域:

  • 辐射瘤学 辐射瘤学
  • 医学物理 医学物理
  • 计算成像技术的成像

背景情况:

  • 自动光束方向优化 (BOO) 对于强度调节放射治疗 (IMRT) 和强度调节质子疗法 (IMPT) 计划质量至关重要.
  • 目前的方法,如组稀疏度优化,需要手动调整来确定最佳数量的束.
  • 需要更快,全自动化的BOO方法来有效地识别最佳光束配置.

研究的目的:

  • 引入和评估一种基于梯度下降的自动BOO的新型路径搜索算法 (PathGD).
  • 将PathGD的效率和剂量性能与现有方法 (GS-FISTA,手动选择) 进行比较.
  • 评估使用PathGD对头癌患者顺序添加光束的剂量学益处.

主要方法:

  • 一个基于梯度下降的路径搜索算法PathGD是为了流动地图优化而开发的,它使用顺序添加光束来优化流动地图.
  • 用PathGD来选择三名头部和部患者的光束配置 (2-4个质子,5-15个光子光束).
  • 通过PathGD生成的图表与来自组稀疏性-FISTA (GS-FISTA) 和手动选择 (MAN) 的图表进行了比较,以计算效率,剂量计和稳定性 (对于质子图表) 来说.

主要成果:

  • 通过PathGD,比GS-FISTA的光束选择速度平均快35%.
  • 路径GD与GS-FISTA计划的CTV覆盖率相匹配,同时显著降低了OAR平均和最大剂量 (平均13.6%).
  • 通过PathGD改进了CTV剂量指标,并减少了最糟糕的OAR剂量,突出了其光束对光束方法的剂量测量优势.

结论:

  • 在IMRT和IMPT方面,PathGD提供了一种高效且在剂量测量上优越的替代方案,与现有的BOO方法相比.
  • 算法的分析每束剂量计成本的能力有助于选择最佳计划.
  • 路径GD的表现强调了光束排列优化的重要性,特别是对于IMPT.