The authors have previously shown the feasibility of using an artificial neural network (ANN) to eliminate the volume average effect (VAE) of scanning ionization chambers (ICs). The purpose of this work was to evaluate the method when applied to beams of different energies (6 and 10 MV) and modalities [flattened (FF) vs unflattened (FFF)], measured with ICs of various sizes.

中文翻译：

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基于神经网络的光子束轮廓反卷积方法的评估。

作者先前已经证明了使用人工神经网络（ANN）消除扫描电离室（IC）的体积平均效应（VAE）的可行性。这项工作的目的是评估该方法应用于不同能量（6和10 MV）的光束和模态[展平（FF）与未展平（FFF）]的情况，并使用各种尺寸的IC进行测量。