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Compressive x-ray material decomposition using structured illumination
Author(s): Angela P. Cuadros; Xu Ma; Gonzalo R. Arce
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Paper Abstract

This manuscript explores a new approach for spectral X-ray tomography that uses K-edge filtering structures to attain spectral and spatially coded illumination which enables the acquisition of compressive measurements for the reconstruction of energy-binned images. The system is coined compressive spectral X-ray imaging (CSXI). A multi-stage algorithm is proposed to solve the non-linear ill-posed problem using sparse and low-rank regularization constraints to exploit the structure of the spectral data cube. The proposed algorithm can reconstruct both the energy binned images as well as the material decomposition of the object given a set of basis materials.

Paper Details

Date Published: 10 September 2019
PDF: 6 pages
Proc. SPIE 11113, Developments in X-Ray Tomography XII, 111131H (10 September 2019); doi: 10.1117/12.2526843
Show Author Affiliations
Angela P. Cuadros, Univ. of Delaware (United States)
Xu Ma, Beijing Institute of Technology (China)
Gonzalo R. Arce, Univ. of Delaware (United States)


Published in SPIE Proceedings Vol. 11113:
Developments in X-Ray Tomography XII
Bert Müller; Ge Wang, Editor(s)

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