基于神经网络的CT扫描人体头部辐射剂量建模

J. Radulović, N. Mijailovic, Vesna Ranković, M. Trajanovic, N. Filipovic
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引用次数: 0

摘要

在本研究中,作者提出了计算机断层扫描(CT)过程中人体头部暴露剂量的测定方法。该方法基于前馈神经网络(FFNN)模型来预测人体头部的照射剂量。构造了具有Levenberg-Marquardt学习的神经网络。训练数据采用蒙特卡罗方法进行仿真。模拟是通过产生随机数来确定光子方向和量化x射线光子与头部组织之间的相互作用来进行的。光子能量光谱用于3DCT扫描仪,x射线管XRS-125-7K-P型。FFNN预测值与仿真得到的预测值基本一致,相关系数在0.99左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling of radiation dose of human head during CT scanning using neural networks
In this study the authors present the method for determination of exposure dose on human head during computer tomography (CT) scanning procedure. The method is based on the use of the feed-forward neural network (FFNN) model to predict the exposure dose on human head. The neural network with Levenberg-Marquardt learning is constructed. The training data are obtained using the Monte Carlo method simulation. The simulation is performed by generating random numbers for determination of photon direction and for quantification of interaction between X-ray photon and head tissue. Spectra of photon energy is used for 3DCT scanner, X-ray tube Model XRS-125-7K-P. The FFNN predicted values are in accordance with the values obtained by the simulation with correlation coefficient around 0.99.
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