  The validation of a previous work on the optimization of material
discrimination in spectral x-ray imaging is reported. Using Monte Carlo
simulations based on the BEAMnrc package, material decomposition was performed
on the projection images of phantoms containing up to three materials. The
simulated projection data was first decomposed into material basis images by
minimizing the z-score between expected and simulated counts. Statistical
analysis was performed for the pixels within the region-of-interest consisting
of contrast material(s) in the BEAMnrc simulations. With the consideration of
scattered radiation and a realistic scanning geometry, the theoretical optima
of energy bin borders provided by the algorithm were shown to have an accuracy
of $\pm$2 keV for the decomposition of 2 and 3 materials. Finally, the
signal-to-noise ratio predicted by the theoretical model was also validated.
The counts per pixel needed for achieving a specific imaging aim can therefore
be estimated using the validated model.
