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Proceedings Paper

Optimal calibration via virtual x-ray imaging for dual-energy techniques: application to glass wool
Author(s): Jean-Michel Letang; N. Freud; Gilles Peix
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Paper Abstract

We present in this paper a technique that makes benefit of a virtual X-ray simulation tool to both assess the optimal spectra and calibrate a dual-energy technique. The proposed method is applied to the selective imaging of glass wool materials. To optimize the choice of energy spectra, a signal-to-noise (SNR) criterion on the materials estimated thickness is derived using a constant absorbed energy constraint in the detector. To study further its reliability, the criterion is related to the measurement quality, expressed by a contrast to noise ratio of the input projections, and to the inversion stability, expressed by a contrast to noise ration of the input projections, and to the inversion stability, expressed by the numerical conditioning of the linear dual-energy attenuation system. Once the choice of energy spectra is settled, apparent thicknesses are modeled as third order polynomials expressed in terms of X-ray attenuation measures. The best polynomial fit and the choice of the degree can again be advantageously assessed using virtual X-ray imaging. A semi-empirical catalog is here used to characterize the X-ray source spectrum, and attenuation coefficients for each corresponding compound substance are obtained from standard databases. After completion of those calibration phases, a glass wool phantom composed of PMMA and glass (combined step wedges) is used to validate using real experimental data the selected dual-energy protocol obtained by virtual X-ray imaging. The worse error on the estimated thickness is about 5% for both the binder and the glass fibers. Quantitative imaging in thickness of glass fibers and binder is finally presented.

Paper Details

Date Published: 1 May 2003
PDF: 11 pages
Proc. SPIE 5132, Sixth International Conference on Quality Control by Artificial Vision, (1 May 2003); doi: 10.1117/12.515145
Show Author Affiliations
Jean-Michel Letang, INSA of Lyon (France)
N. Freud, INSA of Lyon (France)
Gilles Peix, INSA of Lyon (France)

Published in SPIE Proceedings Vol. 5132:
Sixth International Conference on Quality Control by Artificial Vision
Kenneth W. Tobin Jr.; Fabrice Meriaudeau, Editor(s)

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