Reconstruction of multi-energy X-ray computed tomography images of laboratory mice

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Abstract
A new x-ray computed tomography (CT) system is being developed at Oak Ridge National Laboratory to image laboratory mice for the purpose of rapid phenotype screening and identification. One implementation of this CT system allows simultaneous capture of several sets of sinogram data, each having a unique x-ray energy distribution. The goals of this paper are to (1) identify issues associated with the reconstruction of this energy-dependent data and (2) suggest preliminary approaches to address these issues. Due to varying numbers of photon counts within each set, both traditional (filtered backprojection, or FBP) and statistical (maximum likelihood, or ML) tomographic image reconstruction techniques have been applied to the energy-dependent sinogram data. Results of reconstructed images using both algorithms on sinogram data (high- and low-count) are presented. Also, tissue contrast within the energy-dependent images is compared to known x-ray attenuation coefficients of soft tissue (e.g. muscle, bone, and fat).

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