Maximum-likelihood dual-energy tomographic image reconstruction

Jeffrey A. Fessler; Idris A. Elbakri; Predrag Sukovic; Neal H. Clinthorne

doi:10.1117/12.467189

9 May 2002 Maximum-likelihood dual-energy tomographic image reconstruction

Jeffrey A. Fessler, Idris A. Elbakri, Predrag Sukovic, Neal H. Clinthorne

Author Affiliations +

Proceedings Volume 4684, Medical Imaging 2002: Image Processing; (2002) https://doi.org/10.1117/12.467189
Event: Medical Imaging 2002, 2002, San Diego, California, United States

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.

Citation Download Citation

Jeffrey A. Fessler, Idris A. Elbakri, Predrag Sukovic, and Neal H. Clinthorne "Maximum-likelihood dual-energy tomographic image reconstruction", Proc. SPIE 4684, Medical Imaging 2002: Image Processing, (9 May 2002); https://doi.org/10.1117/12.467189

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