GDRR: A GPU Tool for Cone-Beam CT Projection Simulations
X Jia*, H Yan, M Folkerts, S Jiang, University of California, San Deigo, La Jolla, CATU-A-213CD-1 Tuesday 8:00:00 AM - 9:55:00 AM Room: 213CD
Purpose: Realistic calculations of x-ray projection images play an important role in many projects related to CBCT, such as the design of scanners and reconstruction algorithms. However, to yield a desired level of realism it usually requires a tremendously long computational time, which hinders the research process. The purpose of this project is to develop a realistic x-ray projection image simulation package, gDRR, on a computer graphics processing unit (GPU) to achieve both high accuracy and efficiency.
Methods: Primary signals in a projection is computed by GPU-based ray-tracing algorithms, with many features considered, e.g. source energy spectrum, fluence map due to a bowtie filter, and detector response. Scatter signals are obtained by Monte Carlo (MC) simulations on GPU under the aforementioned realistic setup followed by a denoising step. Noise signals are calculated by taking the difference between the MC simulated primary and the ray-tracing primary signals, and the difference between the MC simulated scatter signals and the denoised scatter signals. The noise level is calibrated according to the mAs level in a scan.
Results: The primary signals agree well with results from MC simulations. As for the scatter signals, our MC results for real patient cases are in good agreement with those from EGSnrc with less than 2% relative error using 10 million source photons. Various realistic artifacts can be observed in CBCT images reconstructed from the simulated projections, e.g. beam hardening, scatter, and noise. The computation time per projection is ~20ms for primary signal per energy channel, ~4sec for scatter signal, and 1~2sec for all other steps.
Conclusions: We have developed a complete simulation package on GPU to compute x-ray projections in CBCT. Primary, scatter, and noise signals can be calculated with a high level of realism at a high efficiency.