Comparison of Quadratic- and Median-Based Roughness Penalties for Penalized-Likelihood Sinogram Restoration in Computed Tomography

La Rivière, Patrick J.; Bian, Junguo; Vargas, Phillip A.

doi:https://doi.org/10.1155/IJBI/2006/41380

International Journal of Biomedical Imaging

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Development of Computed Tomography Algorithms

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Volume 2006 | Article ID 041380 | https://doi.org/10.1155/IJBI/2006/41380

Comparison of Quadratic- and Median-Based Roughness Penalties for Penalized-Likelihood Sinogram Restoration in Computed Tomography

Patrick J. La Rivière,¹Junguo Bian,¹and Phillip A. Vargas¹

Received13 Dec 2005

Revised03 Mar 2006

Accepted05 Mar 2006

Published19 Apr 2006

Abstract

We have compared the performance of two different penalty choices for a penalized-likelihood sinogram-restoration strategy we have been developing. One is a quadratic penalty we have employed previously and the other is a new median-based penalty. We compared the approaches to a noniterative adaptive filter that loosely but not explicitly models data statistics. We found that the two approaches produced similar resolution-variance tradeoffs to each other and that they outperformed the adaptive filter in the low-dose regime, which suggests that the particular choice of penalty in our approach may be less important than the fact that we are explicitly modeling data statistics at all. Since the quadratic penalty allows for derivation of an algorithm that is guaranteed to monotonically increase the penalized-likelihood objective function, we find it to be preferable to the median-based penalty.

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Copyright

Copyright © 2006 Patrick J. La Rivière et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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