经典随机耦合模型在对电子设备的电磁脉冲效应进行预测时,边界条件设置在无穷远处,存在短迹线效应问题.采用设置辐射阻抗短迹线调制系数的方法,建立了二端口波混沌腔体短迹线随机耦合模型(Short-Orbit Random Coupling Model,SORCM),统...经典随机耦合模型在对电子设备的电磁脉冲效应进行预测时,边界条件设置在无穷远处,存在短迹线效应问题.采用设置辐射阻抗短迹线调制系数的方法,建立了二端口波混沌腔体短迹线随机耦合模型(Short-Orbit Random Coupling Model,SORCM),统计分析了目标点处感应电压的均方根误差随短迹线最大长度的变化关系.在不同的频段范围内,将SORCM计算结果的统计特性和实验结果进行了对比分析,验证了所建立模型的正确性.和经典随机耦合模型相比,SORCM的计算结果更加接近实测结果,可用于复杂电子设备电磁脉冲效应的预测和分析.展开更多
Cone-beam CT (CBCT) images acquired during radiation treatment can be used to recalculate the dose distribution as well as to confirm the treatment location. However, it is difficult to obtain the electron densities (...Cone-beam CT (CBCT) images acquired during radiation treatment can be used to recalculate the dose distribution as well as to confirm the treatment location. However, it is difficult to obtain the electron densities (EDs) necessary for dose calculation from CBCT images because of the effects of scatter contamination during CBCT image acquisition. This paper presents a mathematical method for converting the pixel values of CBCT images (CBCT values) into Hounsfield units (HUs) of radiation treatment simulation CT (simCT) images for use in radiation treatment planning. CBCT values are converted into HUs by matching the histograms of the CBCT values with the histograms of the HUs for each slice via linear scaling of the CBCT values. For prostate cancer and head-and-neck cancer patients, the EDs obtained from converted CBCT values (mCBCT values) show good agreement with the EDs obtained from HUs, within approximately 3.0%, and the dose calculated on the basis of CBCT images shows good agreement with the dose calculated on the basis of the simCT images, within approximately 2.0%. Because the CBCT values are converted for each slice, this conversion method can account for variation in the CBCT values associated with differences in body size, body shape, and inner tissue structures, as well as in longitudinally displaced positions from the isocenter, unlike conventional methods that use electron density phantoms. This method improves on conventional CBCT-ED conversion and shows considerable potential for improving the accuracy of radiation treatment planning using CBCT images.展开更多
文摘经典随机耦合模型在对电子设备的电磁脉冲效应进行预测时,边界条件设置在无穷远处,存在短迹线效应问题.采用设置辐射阻抗短迹线调制系数的方法,建立了二端口波混沌腔体短迹线随机耦合模型(Short-Orbit Random Coupling Model,SORCM),统计分析了目标点处感应电压的均方根误差随短迹线最大长度的变化关系.在不同的频段范围内,将SORCM计算结果的统计特性和实验结果进行了对比分析,验证了所建立模型的正确性.和经典随机耦合模型相比,SORCM的计算结果更加接近实测结果,可用于复杂电子设备电磁脉冲效应的预测和分析.
文摘Cone-beam CT (CBCT) images acquired during radiation treatment can be used to recalculate the dose distribution as well as to confirm the treatment location. However, it is difficult to obtain the electron densities (EDs) necessary for dose calculation from CBCT images because of the effects of scatter contamination during CBCT image acquisition. This paper presents a mathematical method for converting the pixel values of CBCT images (CBCT values) into Hounsfield units (HUs) of radiation treatment simulation CT (simCT) images for use in radiation treatment planning. CBCT values are converted into HUs by matching the histograms of the CBCT values with the histograms of the HUs for each slice via linear scaling of the CBCT values. For prostate cancer and head-and-neck cancer patients, the EDs obtained from converted CBCT values (mCBCT values) show good agreement with the EDs obtained from HUs, within approximately 3.0%, and the dose calculated on the basis of CBCT images shows good agreement with the dose calculated on the basis of the simCT images, within approximately 2.0%. Because the CBCT values are converted for each slice, this conversion method can account for variation in the CBCT values associated with differences in body size, body shape, and inner tissue structures, as well as in longitudinally displaced positions from the isocenter, unlike conventional methods that use electron density phantoms. This method improves on conventional CBCT-ED conversion and shows considerable potential for improving the accuracy of radiation treatment planning using CBCT images.
