Abstract
An efficient and accurate algorithm for radiation dose evaluation is presented in this paper. Such computations are useful in the radiotherapic treatment planning of tumors. The originality of our approach is to use a neural network which has been trained with several homogeneous environments to deduce the doses in any kind of environment (possibly heterogeneous). Our algorithm is compared in several representative contexts to a reference simulation code in the domain.
Work supported by LCC,CAPM,Région Franche-Comté and Canceropôle Grand- Est.
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Bahi, J.M., Contassot-Vivier, S., Makovicka, L., Martin, É., Sauget, M. (2006). Neural Network Based Algorithm for Radiation Dose Evaluation in Heterogeneous Environments. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840930_81
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DOI: https://doi.org/10.1007/11840930_81
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