Compressive x-ray material decomposition using structured illumination

Angela P. Cuadros; Xu Ma; Gonzalo R. Arce

doi:10.1117/12.2526843

10 September 2019 Compressive x-ray material decomposition using structured illumination

Angela P. Cuadros, Xu Ma, Gonzalo R. Arce

Author Affiliations +

Proceedings Volume 11113, Developments in X-Ray Tomography XII; 111131H (2019) https://doi.org/10.1117/12.2526843
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

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.

Citation Download Citation

Angela P. Cuadros, Xu Ma, and Gonzalo R. Arce "Compressive x-ray material decomposition using structured illumination", Proc. SPIE 11113, Developments in X-Ray Tomography XII, 111131H (10 September 2019); https://doi.org/10.1117/12.2526843

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