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Proceedings Paper

X-ray backscatter radiography with lower open fraction coded masks
Author(s): André A. M. Muñoz; Anna Vella; Matthew J. F. Healy; David W. Lane; Ian Jupp; David Lockley
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Paper Abstract

Single sided radiographic imaging would find great utility for medical, aerospace and security applications. While coded apertures can be used to form such an image from backscattered X-rays they suffer from near field limitations that introduce noise. Several theoretical studies have indicated that for an extended source the images signal to noise ratio may be optimised by using a low open fraction (<0.5) mask. However, few experimental results have been published for such low open fraction patterns and details of their formulation are often unavailable or are ambiguous. In this paper we address this process for two types of low open fraction mask, the dilute URA and the Singer set array. For the dilute URA the procedure for producing multiple 2D array patterns from given 1D binary sequences (Barker codes) is explained. Their point spread functions are calculated and their imaging properties are critically reviewed. These results are then compared to those from the Singer set and experimental exposures are presented for both type of pattern; their prospects for near field imaging are discussed.

Paper Details

Date Published: 7 September 2017
PDF: 17 pages
Proc. SPIE 10393, Radiation Detectors in Medicine, Industry, and National Security XVIII, 103930A (7 September 2017); doi: 10.1117/12.2273784
Show Author Affiliations
André A. M. Muñoz, Cranfield Univ. (United Kingdom)
Anna Vella, Cranfield Univ. (United Kingdom)
Matthew J. F. Healy, Cranfield Univ. (United Kingdom)
David W. Lane, Cranfield Univ. (United Kingdom)
Ian Jupp, Defence Science and Technology Lab. (United Kingdom)
David Lockley, Defence Science and Technology Lab. (United Kingdom)


Published in SPIE Proceedings Vol. 10393:
Radiation Detectors in Medicine, Industry, and National Security XVIII
Gary P. Grim; Lars R. Furenlid; H. Bradford Barber, Editor(s)

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