2 research outputs found
Maximum-Likelihood Dual-Energy TomographicImage Reconstruction
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.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85934/1/Fessler172.pd