26 September 2013 Coding and sampling for compressive x-ray diffraction tomography
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Proceedings Volume 8858, Wavelets and Sparsity XV; 885813 (2013); doi: 10.1117/12.2027128
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States
Abstract
Coded apertures and energy resolving detectors may be used to improve the sampling efficiency of x-ray tomography and increase the physical diversity of x-ray phenomena measured. Coding and decompressive inference enable increased molecular specificity, reduced exposure and scan times. We outline a specific coded aperture x-ray coherent scatter imaging architecture that demonstrates the potential of such schemes. Based on this geometry, we develop a physical model using both a semi-analytic and Monte Carlo-based framework, devise an experimental realization of the system, describe a reconstruction algorithm for estimating the object from raw data, and propose a classification scheme for identifying the material composition of the object at each location
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Joel A. Greenberg, Kalyani Krishnamurthy, Manu Lakshmanan, Kenneth MacCabe, Scott Wolter, Anuj Kapadia, David Brady, "Coding and sampling for compressive x-ray diffraction tomography", Proc. SPIE 8858, Wavelets and Sparsity XV, 885813 (26 September 2013); doi: 10.1117/12.2027128; http://dx.doi.org/10.1117/12.2027128
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KEYWORDS
Sensors

X-rays

Signal to noise ratio

Coded apertures

Photons

X-ray imaging

Monte Carlo methods

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