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Current status and new horizons in Monte Carlo simulation of X-ray CT scanners

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Abstract

With the advent of powerful computers and parallel processing including Grid technology, the use of Monte Carlo (MC) techniques for radiation transport simulation has become the most popular method for modeling radiological imaging systems and particularly X-ray computed tomography (CT). The stochastic nature of involved processes such as X-ray photons generation, interaction with matter and detection makes MC the ideal tool for accurate modeling. MC calculations can be used to assess the impact of different physical design parameters on overall scanner performance, clinical image quality and absorbed dose assessment in CT examinations, which can be difficult or even impossible to estimate by experimental measurements and theoretical analysis. Simulations can also be used to develop and assess correction methods and reconstruction algorithms aiming at improving image quality and quantitative procedures. This paper focuses mainly on recent developments and future trends in X-ray CT MC modeling tools and their areas of application. An overview of existing programs and their useful features will be given together with recent developments in the design of computational anthropomorphic models of the human anatomy. It should be noted that due to limited space, the references contained herein are for illustrative purposes and are not inclusive; no implication that those chosen are better than others not mentioned is intended.

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Acknowledgments

This work was supported by the Swiss National Science Foundation under grant SNSF 3100A0–116547.

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  1. Mohammad Reza Ay

    Present address: Department of Medical Physics and Biomedical Engineering, School of Medicine, Medical Sciences/University of Tehran, Tehran, Iran

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  1. Division of Nuclear Medicine, Geneva University Hospital, 1211, Geneva 4, Switzerland

    Habib Zaidi & Mohammad Reza Ay

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Correspondence to Habib Zaidi.

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Zaidi, H., Ay, M.R. Current status and new horizons in Monte Carlo simulation of X-ray CT scanners. Med Bio Eng Comput 45, 809–817 (2007). https://doi.org/10.1007/s11517-007-0207-9

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