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Proceedings Paper

Accelerated coordinate descent methods for Bayesian reconstruction using ordered subsets of projection data
Author(s): Soo-Jin Lee
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Paper Abstract

The ordered subsets (OS) algorithm1 has enjoyed considerable interest for accelerating the well-known EM reconstruction algorithm for emission tomography and has recently found widespread use in clinical practice. This is primarily due to the fact that, while retaining the advantages of EM, the OS-EM algorithm can be easily implemented by slightly modifying the existing EM algorithm. The OS algorithm has also been applied1 with the one-step-late (OSL) algorithm,2 which provides maximum a posteriori estimation based on Gibbs priors. Unfortunately, however, the OSL approach is known to be unstable when the smoothing parameter that weights the prior relative to the likelihood is relatively large. In this work, we note that the OS principle can be applied to any algorithm that involves calculation of a sum over project indices, and show that it can also be applied to a generalized EM algorithm with useful quadratic priors. In this case, the algorithm is given in the form of iterated conditional modes (ICM), which is essentially a coordinate-wise descent method, and provides a number of important advantages. We also show that, by scaling the smoothing parameter in a principled way, the degree of smoothness is reconstructed images, which appears to vary depending on the number of subsets, can be efficiently matched for different numbers of subsets. Our experimental results indicate that the OS-ICM algorithm along with the method of scaling the smoothing parameter provides robust results as well as a substantial acceleration.

Paper Details

Date Published: 4 October 2000
PDF: 12 pages
Proc. SPIE 4121, Mathematical Modeling, Estimation, and Imaging, (4 October 2000); doi: 10.1117/12.402437
Show Author Affiliations
Soo-Jin Lee, Paichai Univ. (South Korea)

Published in SPIE Proceedings Vol. 4121:
Mathematical Modeling, Estimation, and Imaging
David C. Wilson; Hemant D. Tagare; Fred L. Bookstein; Francoise J. Preteux; Edward R. Dougherty, Editor(s)

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