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Artificial neural network modelling of megavoltage photon dose distributions

Steve W Blake

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An artificial neural network (NN) has been used to model the two-dimensional dose distributions from a Varian 2100C linac. The network was trained using depth dose data for 6 and 10 MV x-rays, collected during the linac commissioning phase. During training, the number of iterations and hidden nodes was adjusted manually until acceptable agreement between measured and predicted data was obtained. In order to validate the network a subset of the data was set aside and not used for training. This enabled the performance of the network to be investigated in terms of generalization and accuracy, together with its ability to interpolate between different field sizes and positions in the beam. Finally, the network was used to generate data points over a 2D grid so that isodose distributions could be visualized. Good agreement was found between measured data and that produced by the trained neural network.


PACS

87.53.Bn Dosimetry/exposure assessment

07.05.Mh Neural networks, fuzzy logic, artificial intelligence

Subjects

Instrumentation and measurement

Medical physics

Dates

Issue 12 (21 June 2004)

Received 13 October 2003, in final form 3 March 2004

Published 26 May 2004



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