Combining Monte Carlo methods with coherent wave optics for the simulation of phase-sensitive X-ray imaging

Abstract

Phase-sensitive X-ray imaging shows a high sensitivity towards electron density variations, making it well suited for imaging of soft tissue matter. However, there are still open questions about the details of the image formation process. Here, a framework for numerical simulations of phase-sensitive X-ray imaging is presented, which takes both particle-and wave-like properties of X-rays into consideration. A split approach is presented where we combine a Monte Carlo method (MC) based sample part with a wave optics simulation based propagation part, leading to a framework that takes both particle-and wavelike properties into account. The framework can be adapted to different phasesensitive imaging methods and has been validated through comparisons with experiments for grating interferometry and propagation-based imaging. The validation of the framework shows that the combination of wave optics and MC has been successfully implemented and yields good agreement between measurements and simulations. This demonstrates that the physical processes relevant for developing a deeper understanding of scattering in the context of phase-sensitive imaging are modelled in a sufficiently accurate manner. The framework can be used for the simulation of phase-sensitive X-ray imaging, for instance for the simulation of grating interferometry or propagation-based imaging.

Visibility simulation of realistic grating interferometers including grating geometries and energy spectra

“…The simulation results of the setup presented in this work are based on a well established waveoptics simulation approach that is commonly used in qualitatively simulating X-ray grating interferometers [12][13][14][15] and was adapted to simulate the nGI setup at ICON. Its fundamental idea is to define an incoming wave front at G1 (D G1 (y)) and propagate it using a free space propagator (P real (y, d, λ)) based on Fresnel interference to the fractional Talbot distance.…”

“…The key feature that most work was concerned with is the spectral distribution of the X-ray tube source and its impact on the performance of the grating interferometer [12][13][14] or even the actual simulation of images [15]. Tube sources emit a large range of energies and the understanding of the impact of spectral distributions on the visibility is often driven by increasing the setup performance and thus lowering the dose for patients in medical applications.…”

Big-data x-ray phase contrast imaging simulation challenges

“…al. 3 Both efforts propose leveraging Monte Carlo methods to create XPCI images which show good agreement with experimental data. Cipiccia et.…”

“…Unfortunately, the survey could not find any efforts in large-scale simulation as most efforts either restricted the simulation to very small fields-of-view, compressed information in object-space, short propagation lengths, or any combination thereof. [1][2][3][4] Work by Peterzol et. al.…”

“…For this work, it was decided that an incremental approach to building a complex system was most reasonable to help identify challenges early-on as there exists extensive studies on small-scale simulations. [1][2][3][4] One of the appealing features of XPCI is its greater sensitivity to density and material variations; however, greater sensitivity in a system implies that a greater level of caution is needed when designing algorithms for a BDXPCI simulation tool. Particular caution must be exercised when attempting to design algorithms that will operate on big data, as a small error can propagate through the algorithm-increasing as more information is processed by the method.…”