  X-ray dose constantly gains interest in the interventional suite. With dose
being generally difficult to monitor reliably, fast computational methods are
desirable. A major drawback of the gold standard based on Monte Carlo (MC)
methods is its computational complexity. Besides common variance reduction
techniques, filter approaches are often applied to achieve conclusive results
within a fraction of time. Inspired by these methods, we propose a novel
approach. We down-sample the target volume based on the fraction of mass,
simulate the imaging situation, and then revert the down-sampling. To this end,
the dose is weighted by the mass energy absorption, up-sampled, and distributed
using a guided filter. Eventually, the weighting is inverted resulting in
accurate high resolution dose distributions. The approach has the potential to
considerably speed-up MC simulations since less photons and boundary checks are
necessary. First experiments substantiate these assumptions. We achieve a
median accuracy of 96.7 % to 97.4 % of the dose estimation with the proposed
method and a down-sampling factor of 8 and 4, respectively. While maintaining a
high accuracy, the proposed method provides for a tenfold speed-up. The overall
findings suggest the conclusion that the proposed method has the potential to
allow for further efficiency.
