Artificial Neural Network Model for Spectral Construction of a Linear Accelerator Megavoltage Photon Beam

Sabir Hussain
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引用次数: 5

Abstract

In photon radiotherapy, one of the most critical parameters for the delivery of highly target-conformal dose to the target volume is the determination of the energy spectra incident on the surface of the target volume. This paper proposes an artificial neural network (ANN) model for the determination of megavoltage photon beams spectra. We have computed bremsstrahlung spectra of 4 to 25 MV beams for different medical linear accelerators. The ANN model is trained with thousands of data sets obtained from the Monte Carlo (MC) constructed spectra data of different energies. The computed spectra from the ANN model are verified by its comparison with published Monte Carlo spectra data and we have found an excellent agreement in the results. A major advantage of the ANN model is its ability of instantaneous data analysis after learning phase, enabling automated data analysis within short period for dose optimization with greater accuracy.
线性加速器超高电压光子光束光谱构建的人工神经网络模型
在光子放射治疗中,将高靶适形剂量传递到靶体的最关键参数之一是入射到靶体表面的能谱的确定。本文提出了一种用于测定超高电压光子光束光谱的人工神经网络模型。我们计算了不同医用直线加速器的4 ~ 25mv光束的轫致辐射谱。利用蒙特卡罗(MC)构造的不同能量的光谱数据得到的数千个数据集对人工神经网络模型进行训练。通过与已发表的蒙特卡罗光谱数据的比较,验证了人工神经网络模型计算的光谱,结果非常吻合。人工神经网络模型的一个主要优点是其在学习阶段后的瞬时数据分析能力,可以在短时间内自动分析数据,以更高的精度进行剂量优化。
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