Alternating update penalized-likelihood image reconstruction for x-ray fluorescence computed tomography

Patrick J. La Rivière; Phillip Vargas

doi:10.1117/12.682558

7 September 2006 Alternating update penalized-likelihood image reconstruction for x-ray fluorescence computed tomography

Patrick J. La Rivière, Phillip Vargas

Author Affiliations +

Proceedings Volume 6318, Developments in X-Ray Tomography V; 63180Z (2006) https://doi.org/10.1117/12.682558
Event: SPIE Optics + Photonics, 2006, San Diego, California, United States

Abstract

In this work, we continue to pursue penalized-likelihood image reconstruction algorithms for X-ray fluorescence computed tomography (XFCT) when the attenuation maps at the energies of the fluorescence X-rays are unknown. Our previous approach, while yielding good results, was somewhat heuristic and did not necessarily correspond to maximization of a predefined penalized-likelihood objective function. Here we present an iterative algorithm that is guaranteed to increase a predefined objective function at each iteration. The approach alternates between updating the distribution of a given element and updating the attenuation map for that element's fluorescence X-rays. We apply the algorithm to simulated numerical data as well as to real synchrotron data.

Citation Download Citation

Patrick J. La Rivière and Phillip Vargas "Alternating update penalized-likelihood image reconstruction for x-ray fluorescence computed tomography", Proc. SPIE 6318, Developments in X-Ray Tomography V, 63180Z (7 September 2006); https://doi.org/10.1117/12.682558

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