  Computed Tomography (CT) imaging is one of the most influential diagnostic
methods. In clinical reconstruction, an effective energy is used instead of
total X-ray spectrum. This approximation causes an accuracy decline. To
increase the contrast, single source or dual source dual energy CT can be used
to reach optimal values of tissue differentiation. However, these
infrastructures are still at the laboratory level, and their safeties for
patients are still yet to mature. Therefore, computer modelling of DECT could
be used. We propose a novel post-processing approach for converting a total
X-ray spectrum into irregular intervals of quantized energy. We simulate a
phantom in GATE/GEANT4 and irradiate it based on CT configuration. Inverse
Radon transform is applied to the acquired sinogram to construct the
Pixel-based Attenuation Matrix (PAM). To construct images represented by each
interval, water attenuation coefficient of the interval is extracted from NIST
and used in the Hounsfield unit (HU) scale in conjunction with PAM. The CT
image is modified by using of an associated normalized photon flux and
calculated HU corresponding to the interval. We demonstrate the proposed method
efficiency via complexity analysis, using absolute and relative complexities,
entropy measures, Kolmogorov complexity, morphological richness, and
quantitative segmentation criteria associated with standard fuzzy C-means. The
irregularity of the modified CT images decreases over the simulated ones.
