Noninvasive material discrimination using spectral radiography and an inverse problem approach




Gilbert, Andrew James

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Noninvasive material discrimination of an arbitrary object is applicable to a wide range of fields, including medical scans, security inspections, nuclear safeguards, and nuclear material accountancy. In this work, we present an algorithmic framework to accurately determine material compositions from multi-spectral X-ray and neutron radiography. The algorithm uses an inverse problem approach and regularization, which amounts to adding information to the problem; stabilizing the solution so that accurate material estimations can be made from a problem that would otherwise be intractable. First, we show the utility of the algorithm with simulated inspections of small objects, such as baggage, for small quantities of high-atomic-numbered materials (i.e. plutonium). The algorithm shows excellent sensitivity to shielded plutonium in a scan using an X-ray detector that can bin X-rays by energy. We present here a method to adaptively weight the regularization term, obtaining an optimal solution with minimal user input. Second, we explore material discrimination with high-energy, multiple-energy X-ray. Experimental X-ray data is obtained here and accurate discrimination of steel among lower-atomic-numbered materials is shown. Accurate modeling of the inspection system physics is found to be essential for accurate material estimations with this data, especially the detector response and the scattered flux on the image plane. Third, we explore the use of neutron radiography as complementary to X-ray radiography for the inspection of nuclear material storage containers. Utility of this extra data is shown, especially in detecting a hypothetical attempt to divert material. We present a method to choose inspection system design parameters (i.e. source energy and detector thickness) a priori by using the Cramér-Rao lower bound as a measure of resulting material estimation accuracy. Finally, we present methodology to use tomography data obtained with an energy discriminating detector for direct reconstruction of material attenuation coefficients.


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