21 May 2004 Alternating minimization multigrid algorithms for transmission tomography
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Abstract
The problem of image formation for X-ray transmission tomography is formulated as a statistical inverse problem. The maximum likelihood estimate of the attenuation function is sought. Using convex optimization methods, maximizing the loglikelihood functional is equivalent to a double minimization of I-divergence, one of the minimizations being over the attenuation function. Restricting the minimization over the attenuation function to a coarse grid component forms the basis for a multigrid algorithm that is guaranteed to monotonically decrease the I-divergence at every iteration on every scale.
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Joseph A. O'Sullivan, Jasenka Benac, "Alternating minimization multigrid algorithms for transmission tomography", Proc. SPIE 5299, Computational Imaging II, (21 May 2004); doi: 10.1117/12.537508; https://doi.org/10.1117/12.537508
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