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Monte Carlo simulation of projections in computed tomography

Published online by Cambridge University Press:  29 February 2012

B. Chyba
Affiliation:
Vienna University of Technology, Vienna, Austria
M. Mantler*
Affiliation:
Vienna University of Technology, Vienna, Austria
M. Reiter
Affiliation:
Upper Austria University of Applied Sciences, Wels, Austria
*
a)Author to whom correspondence should be addressed. Electronic mail: [email protected]

Abstract

Results from Monte Carlo simulations of two-dimensional projections for a simple real sample (an aluminium cube with a cylindrical hole filled by air or steel) in a realistic experimental environment are presented. A meaningful comparison with measurements was therefore possible. Coherent and incoherent scattering as well as excitation of fluorescent radiation are accounted for; multiple sequences of these interactions are followed up to a selectable order. Such simulations are important aids to modern metrological applications of computed tomography where the dimensional accuracy of hidden or inaccessible components of work pieces is determined. The complex process requires a high level of optimization of the instrumental parameters for each sample type whereby the accurate simulation of the physical interactions between X-rays and the sample material is a supplement and alternative to time consuming measurements.

Type
X-Ray Fluorescence
Copyright
Copyright © Cambridge University Press 2008

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References

Brunetti, A., Sanchez del Rio, M., Golosio, B., Simionovici, A., and Somogyi, A. (2004). “A library for X-ray–matter interaction cross sections for X-ray fluorescence applications,” Spectrochim. Acta, Part B SAASBH 10.1016/j.sab.2004.03.014 59, 17251731.CrossRefGoogle Scholar
Chantler, C. T., Olsen, K., Dragoset, R. A., Chang, J., Kishore, A. R., Kotochigova, S. A., and Zucker, D. S. (2005). X-Ray Form Factor, Attenuation and Scattering Tables (version 2.1) 〈http://physics.nist.gov/ffast〉.Google Scholar
Ebel, H. (2006). “Fundamental parameter programs: Algorithms for the description of K, L and M spectra of X-ray tubes,” Adv. X-Ray Anal. AXRAAA 49, 267273.Google Scholar
Elam, W. T., Ravel, B. D., and Sieber, J. R. (2002). “A new atomic database for X-ray spectroscopic calculations,” Radiat. Phys. Chem. RPCHDM 10.1016/S0969-806X(01)00227-4 63, 121128.CrossRefGoogle Scholar
Mantler, M., Willis, J. P., Lachance, G. R., Vrebos, B. A. R., Mauser, K.-E., Kawahara, N., Rousseau, R. M., and Brouwer, P. N. (2006). “Quantitative Analysis,” in Handbook of Practical X-Ray Fluorescence Analysis, edited by Beckhoff, B., Kanngießer, B., Langhoff, N., Wedell, R., and Wolff, H. (Springer, Berlin), pp. 309429.CrossRefGoogle Scholar
Radon, J. (1917). Bericht Sächsische Akademie der Wissenschaften (Saxon Academy of Sciences, Leipzig), Vol. 69, pp. 262267.Google Scholar