In this paper the use of Bayes rules and interpolation functions is proposed in order to generate three-dimensional artificial neural cells incorporating realistic biological neural shapes. A conditional vectorial stochastic grammar has been developed to control and facilitate the parallel growth of branching. A L-parser (parser to L-Systems) has also been developed to guarantee that the grammar is free from mistakes before its use. This parser has also the function to generate a group of points corresponding to the morphologic structure of a neural cell. These points are visualized in a three-dimensional viewer especially developed to show the neural cell generated.
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