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Proceedings Paper

Monte Carlo simulations of a novel coherent scatter materials discrimination system
Author(s): Laila Hassan; Sean Starr-Baier; C. A. MacDonald; Jonathan C. Petruccelli
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Paper Abstract

X-ray coherent scatter imaging has the potential to improve the detection of liquid and powder materials of concern in security screening. While x-ray attenuation is dependent on atomic number, coherent scatter is highly dependent on the characteristic angle for the target material, and thus offers an additional discrimination. Conventional coherent scatter analysis requires pixel-by-pixel scanning, and so could be prohibitively slow for security applications. A novel slot scan system has been developed to provide rapid imaging of the coherent scatter at selected angles of interest, simultaneously with the conventional absorption images. Prior experimental results showed promising capability. In this work, Monte Carlo simulations were performed to assess discrimination capability and provide system optimization. Simulation analysis performed using the measured ring profiles for an array of powders and liquids, including water, ethanol and peroxide. For example, simulations yielded a signal-to-background ratio of 1.63±0.08 for a sample consisting of two 10 mm diameter vials, one containing ethanol (signal) and one water (background). This high SBR value is due to the high angular separation of the coherent scatter between the two liquids. The results indicate that the addition of coherent scatter information to single or dual energy attenuation images improves the discrimination of materials of interest.

Paper Details

Date Published: 1 May 2017
PDF: 9 pages
Proc. SPIE 10187, Anomaly Detection and Imaging with X-Rays (ADIX) II, 1018706 (1 May 2017); doi: 10.1117/12.2262895
Show Author Affiliations
Laila Hassan, Univ. at Albany (United States)
Sean Starr-Baier, Univ. at Albany (United States)
C. A. MacDonald, Univ. at Albany (United States)
Jonathan C. Petruccelli, Univ. at Albany (United States)


Published in SPIE Proceedings Vol. 10187:
Anomaly Detection and Imaging with X-Rays (ADIX) II
Amit Ashok; Edward D. Franco; Michael E. Gehm; Mark A. Neifeld, Editor(s)

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