This work pertains to our original statistical model-based iterative reconstruction concept for medical computed tomography utilizing the flying focal spot. It is based on a continuous-to-continuous data model, with the forward model formulated as a shift-invariant system. The reconstruction methodology resembles the single-slice rebinning concept, which falls under the so-called "nutating" reconstruction algorithms. This approach facilitates the implementation of an unconventional solution to mitigate the most significant noise artifacts. Although the distribution of these noises is random, it is inconsequential in the presented case. Our enhanced method introduces a novel approach to noise identification and reduction, leveraging the iterative reconstruction technique. Additionally, this methodology exhibits versatility, making it applicable to various other iterative reconstruction methods.