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Proceedings Paper

Maximum-likelihood dual-energy tomographic image reconstruction
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Paper Abstract

Dual-energy (DE) X-ray computed tomography (CT) has shown promise for material characterization and for providing quantitatively accurate CT values in a variety of applications. However, DE-CT has not been used routinely in medicine to date, primarily due to dose considerations. Most methods for DE-CT have used the filtered backprojection method for image reconstruction, leading to suboptimal noise/dose properties. This paper describes a statistical (maximum-likelihood) method for dual-energy X-ray CT that accommodates a wide variety of potential system configurations and measurement noise models. Regularized methods (such as penalized-likelihood or Bayesian estimation) are straightforward extensions. One version of the algorithm monotonically decreases the negative log-likelihood cost function each iteration. An ordered-subsets variation of the algorithm provides a fast and practical version.

Paper Details

Date Published: 9 May 2002
PDF: 12 pages
Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); doi: 10.1117/12.467189
Show Author Affiliations
Jeffrey A. Fessler, Univ. of Michigan (United States)
Idris A. Elbakri, Univ. of Michigan (United States)
Predrag Sukovic, Univ. of Michigan (United States)
Neal H. Clinthorne, Univ. of Michigan (United States)

Published in SPIE Proceedings Vol. 4684:
Medical Imaging 2002: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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