Computational scatter correction in near real-time with a fast Monte Carlo photon transport model for high-resolution flat-panel CT

In computed tomography (CT), scattering causes server quality degradation of the reconstructed CT images by introducing streaks and cupping artifacts which reduce the detectability of low contrast objects. Monte Carlo (MC) simulation is considered the most accurate approach for scatter estimation. However, the existing MC estimators are computationally expensive, especially for high-resolution flat-panel CT. In this paper, we propose a fast and accurate MC photon transport model which describes the physics within the 1 keV to 1 MeV range using multiple controllable key parameters. Based on this model, scatter computation for a single projection can be completed within a range of a few seconds under well-defined model parameters. Smoothing and interpolation are performed on the estimated scatter to accelerate the scatter calculation without compromising accuracy too much compared to measured near scatter-free projection images. Combining the fast scatter estimation with the filtered backprojection (FBP), scatter correction is performed effectively in an iterative manner. To evaluate the proposed MC model, we have conducted extensive experiments on the simulated data and real-world high-resolution flat-panel CT. Compared to the state-of-the-art MC simulators, the proposed MC model achieved a 15 × acceleration on a single-GPU compared to the GPU implementation of the Penelope simulator (MCGPU) utilizing several acceleration techniques, and a 202 × speed-up on a multi-GPU system compared to the multi-threaded state-of-the-art EGSnrc MC simulator. Furthermore, it is shown that for high-resolution images, scatter correction with sufficient accuracy is accomplished within one to three iterations using a FBP and the proposed fast MC photon transport model.