Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations

Maria Thomsen; E.B. Knudsen; Peter Kjær Willendrup; M. Bech; M. Willner; F. Pfeiffer; M. Poulsen; Kim Lefmann; Robert Krarup Feidenhans'l

doi:10.1016/j.nimb.2014.10.015

Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations

Maria Thomsen, E.B. Knudsen, Peter Kjær Willendrup, M. Bech, M. Willner, F. Pfeiffer, M. Poulsen, Kim Lefmann, Robert Krarup Feidenhans'l

7 Citations (Scopus)

Abstract

We show how radiological images of both single and multi material samples can be simulated using the Monte Carlo simulation tool McXtrace and how these images can be used to make a three dimensional reconstruction. Good numerical agreement between the X-ray attenuation coefficient in experimental and simulated data can be obtained, which allows us to use simulated projections in the linearisation procedure for single material samples and in that way reduce beam hardening artefacts. The simulations can be used to predict beam hardening artefacts in multi material samples with complex geometry, illustrated with an example. Linearisation requires knowledge about the X-ray transmission at varying sample thickness, but in some cases homogeneous calibration phantoms are hard to manufacture, which affects the accuracy of the calibration. Using simulated data overcomes the manufacturing problems and in that way improves the calibration.

Original language	English
Journal	Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms
Volume	342
Pages (from-to)	314-320
Number of pages	7
ISSN	0168-583X
DOIs	https://doi.org/10.1016/j.nimb.2014.10.015
Publication status	Published - 1 Jan 2015

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Thomsen, M., Knudsen, E. B., Willendrup, P. K., Bech, M., Willner, M., Pfeiffer, F., Poulsen, M., Lefmann, K., & Feidenhans'l, R. K. (2015). Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 342, 314-320. https://doi.org/10.1016/j.nimb.2014.10.015

Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations. / Thomsen, Maria; Knudsen, E.B.; Willendrup, Peter Kjær et al.
In: Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, Vol. 342, 01.01.2015, p. 314-320.

Research output: Contribution to journal › Journal article › Research › peer-review

Thomsen, M, Knudsen, EB, Willendrup, PK, Bech, M, Willner, M, Pfeiffer, F, Poulsen, M, Lefmann, K & Feidenhans'l, RK 2015, 'Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations', Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, vol. 342, pp. 314-320. https://doi.org/10.1016/j.nimb.2014.10.015

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abstract = "We show how radiological images of both single and multi material samples can be simulated using the Monte Carlo simulation tool McXtrace and how these images can be used to make a three dimensional reconstruction. Good numerical agreement between the X-ray attenuation coefficient in experimental and simulated data can be obtained, which allows us to use simulated projections in the linearisation procedure for single material samples and in that way reduce beam hardening artefacts. The simulations can be used to predict beam hardening artefacts in multi material samples with complex geometry, illustrated with an example. Linearisation requires knowledge about the X-ray transmission at varying sample thickness, but in some cases homogeneous calibration phantoms are hard to manufacture, which affects the accuracy of the calibration. Using simulated data overcomes the manufacturing problems and in that way improves the calibration.",

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AU - Thomsen, Maria

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AU - Willner, M.

AU - Pfeiffer, F.

AU - Poulsen, M.

AU - Lefmann, Kim

AU - Feidenhans'l, Robert Krarup

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Prediction of beam hardening artefacts in computed tomography using Monte Carlo simulations

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