An analytical simulation method for X-ray fluorescence computed tomography. (May 2020)

• Record Type: Journal Article
• Authors: Gao, Bo; Laforce, Brecht; Dhaene, Jelle; Vincze, Laszlo; Van Hoorebeke, Luc; Boone, Matthieu N.
• Is Part Of: Radiation physics and chemistry. Volume 170(2020:May)
• Publication Date: 2020-05
• Subjects: X-ray fluorescence computed tomography (XFCT) -- Analytical simulation method -- GPU-Accelerated computing; Radiation chemistry -- Periodicals; Radiometry -- Periodicals; Radiation -- Periodicals; Chimie sous rayonnement -- Périodiques; 539.2
• DOI: 10.1016/j.radphyschem.2019.108622
• Languages: English
• ISSNs: 0969-806X

Abstract

Abstract: X-ray Fluorescence Computed Tomography (XFCT) is an emerging imaging technique that provides elemental distribution in objects non-invasively. To predict and optimize the experimental outcome of XFCT, data generated by Monte Carlo (MC) simulation is usually used. However, MC codes typically require extended computing times to generate sufficient data. In this paper, we report an XFCT simulation method based on analytical computation. By implementing it in GPU, the time required for the simulation of fluorescence sinograms has been sharply reduced. Through comparing the data generated by the technique presented here with data obtained through other approaches, its validity have been verified. It is expected that the simulation method proposed here could serve as a supporting tool for XFCT in aspects such as optimizing the scanning parameters for XFCT, confirming the feasibility of sample studied by XFCT and developing novel XFCT reconstruction algorithms. Highlights: Analytical simulation can drastically accelerate the simulation of XFCT. Analytical simulation of XFCT can produce results close to those of Monte Carlo code. Difference between simulation and experimental data is caused by uncertainties in lab. Analytical simulation method could serve as a supporting tool for XFCT experiments.