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Monte Carlo X-Ray Tube Simulation for CBCT: Primary Source Phase Space Compression

G Bootsma1*, H Nordstrom2 , M Eriksson2 , D Jaffray1 , (1) University Health Network, Toronto, ON, Canada (2) Elekta Instruments AB, Stockholm, Sweden


(Sunday, 7/14/2019) 3:30 PM - 4:00 PM

Room: Exhibit Hall | Forum 9

Purpose: Monte Carlo (MC) simulations are a powerful and useful tool for improving image quality in x-ray imaging modalities. An accurate x-ray source model is essential to a MC model for CBCT but can be difficult to implement on a GPU while maintaining efficiency and memory constraints. A statistical analysis of the primary photon distribution from a MC x-ray tube simulation is completed and used to create a compact source model for use in CBCT MC simulations.

Methods: MC simulations of an x-ray tube were carried out using a modified version of BEAMnrc. A phase space (PHSP) file was collected at the exit of the tube and photons sorted into three categories: primary, tube scatter, or off-focal radiation. A PCA whitening transforms was calculated using the covariance matrix of the primary PHSP components (energy, position, and direction) and used to transform the PHSP data. A set of 5 quantile functions were created from the transformed PHSP data and sampled using MC techniques to simulate an energy fluence image.

Results: The statistical analysis showed the primary PHSP had correlations between position and direction which were reduced by using the PCA whitening transform allowing the creation of 5 quantile functions from the marginalized probability distributions functions of the transformed PHSP components. The mean absolute error of the energy fluence image when compared to the BEAMnrc data was 1.2%. When the data is untransformed the error was 26.6%.

Conclusion: Our automated method reduces the memory required to accurately simulate a x-ray source on a GPU MC system. Instead of loading a pre-computed phase-space or multivariate quantile function a set of 5 quantile functions and a transform can be loaded and sampled from. This method reduces the memory requirements by greater than 5 orders of magnitude, going from gigabytes of data to kilobytes.

Funding Support, Disclosures, and Conflict of Interest: Funding was received from Elekta, no Elekta products or materials were tested or evaluated in the submission.


Monte Carlo, X Rays, Cone-beam CT


IM- X-ray: Development (new technology and techniques)

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