An efficient scatter correction algorithm based on pre-reconstructed images of contrast enhancement and sparse-viewed Monte Carlo simulation

X-ray scatter is a major degrading factor in x-ray cone beam (CB) CT imaging. In the scatter corrections by using Monte Carlo (MC) simulation, the initial MC modeling is not accurate based on the scatter-polluted volume images, thus the correction has to be performed iteratively, which is one of the reasons that MC based correction is computational demanding. In this paper, we found a relationship that the ratio of I_S (scatter) to I _P+S (primary plus scatter) can be approximated by the weighted data in Radon space. On this basis, we develop a strategy called Projection Contrast Enhancement based Pre-Correction (PCEPC). PCEPC is efficient, achieving a scatter pre-correction with enhanced image Quality (Q) of ∼0.7 (Q=1 for scatter-free images; Q=0 for scatter-contaminated images without correction). By using the results of PCEPC, more accurate MC modeling on the scanned object is feasible with less iterations or even in a non-iterative way, namely as the PCEPC-MC method. An exemplary non-iterative PCEPC-MC is implemented, in which the scatter fluence of eighteen views equally distributed over 2π is simulated by MC toolkit EGSnrc, enhancing the Q further to ∼0.8.