Fast approximation of algebraic reconstruction methods for tomography

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
Kees Joost Batenburg, Linda Plantagie

Abstract

Most reconstruction algorithms for transmission tomography can be subdivided in two classes: variants of Filtered Backprojection (FBP) and iterative algebraic methods. Filtered backprojection is very fast and yields accurate results when a large number of projections are available, with high SNR and a full angular range. Algebraic methods require much more computation time, yet they are more flexible in dealing with limited data problems and noise. In this paper we propose an algorithm that combines the best of these two approaches: for a given linear algebraic method, a filter is computed that can be used within the FBP algorithm. The FBP reconstructions that result from using this filter strongly resemble the algebraic reconstructions and have many of their favorable properties, while the required reconstruction time is similar to standard-FBP. Based on a series of experiments, for both simulation data and experimental data, we demonstrate the merits of the proposed algorithm.

References

Oct 13, 2006·Journal of Structural Biology·Daniel Castaño DíezAchilleas S Frangakis
Jan 1, 1982·IEEE Transactions on Medical Imaging·P M Joseph
Jul 5, 2008·IEEE Transactions on Medical Imaging·Jens Gregor, Thomas Benson

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Citations

Jul 30, 2014·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Daniel M Pelt, Kees Joost Batenburg
Feb 1, 2014·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Geert Van EyndhovenJan Sijbers
Jan 10, 2018·BioMed Research International·C O S SorzanoJ M Carazo
Dec 23, 2016·Advanced Structural and Chemical Imaging·Daniël M Pelt, Vincent De Andrade
Oct 4, 2020·Scientific Reports·Minna BührerFederica Marone

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