1 July 2006 Penalized-likelihood image reconstruction for x-ray fluorescence computed tomography
Patrick Jean La Rivière, David M. Billmire, Phillip Vargas, Mark L. Rivers, Stephen R. Sutton
Author Affiliations +
Abstract
X-ray fluorescence computed tomography (XFCT) allows for the reconstruction of the distribution of elements within a sample from measurements of fluorescence x rays produced by irradiation of the sample with monochromatic synchrotron radiation. XFCT is not a transmission tomography modality, but rather a stimulated emission tomography modality; thus correction for attenuation of the incident and fluorescence photons is essential if accurate images are to be obtained. This is challenging because the attenuation map is, in general, known only at the stimulating beam energy and not at the various fluorescence energies of interest. We make use of empirically fitted analytic expressions for x-ray attenuation coefficients to express the unknown attenuation maps as linear combinations of known quantities and the unknown elemental concentrations of interest. We then develop an iterative image reconstruction algorithm based on penalized-likelihood methods that have been developed for medical emission tomography. Studies with numerical phantoms indicate that the approach is able to produce qualitatively and quantitatively accurate reconstructed images even in the face of severe attenuation. We also apply the method to real synchrotron-acquired data and demonstrate a marked improvement in image quality relative to filtered backprojection reconstruction.
©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)
Patrick Jean La Rivière, David M. Billmire, Phillip Vargas, Mark L. Rivers, and Stephen R. Sutton "Penalized-likelihood image reconstruction for x-ray fluorescence computed tomography," Optical Engineering 45(7), 077005 (1 July 2006). https://doi.org/10.1117/1.2227273
Published: 1 July 2006
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CITATIONS
Cited by 44 scholarly publications and 3 patents.
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KEYWORDS
Signal attenuation

Luminescence

Sensors

Reconstruction algorithms

Image restoration

Algorithm development

Tomography

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