Neural network based algorithm for radiation dose evaluation in heterogeneous environments

Authors:
Jacques M. Bahi;Sylvain Contassot-Vivier;Libor Makovicka;Éric Martin;Marc Sauget
Affiliations:
Laboratoire d'Informatique de Franche-Comté, IUT Belfort-Montbéliard, University of Franche-Comté, Belfort, France;Laboratoire d'Informatique de Franche-Comté, IUT Belfort-Montbéliard, University of Franche-Comté, Belfort, France;CREST Femto-ST, IUT Belfort-Montbéliard, Portes du Jura, University of Franche-Comté, Montbéliard, France;CREST Femto-ST, IUT Belfort-Montbéliard, Portes du Jura, University of Franche-Comté, Montbéliard, France;Laboratoire d'Informatique de Franche-Comté, IUT Belfort-Montbéliard, University of Franche-Comté, Belfort, France
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

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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.