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

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 phen otype screening and identification. One implementation of this CT system al lows simultaneous capture of several sets of sinogram data, each having a u nique x-ray energy distribution. The goals of this paper are to (1) identif y issues associated with the reconstruction of this energy-dependent data a nd (2) suggest preliminary approaches to address these issues. Due to varyi ng numbers of photon counts within each set, both traditional (filtered bac kprojection, or FBP) and statistical (maximum likelihood, or ML) tomographi c image reconstruction techniques have been applied to the energy-dependent sinogram data. Results of reconstructed images using both algorithms on si nogram data (high- and low-count) are presented. Also, tissue contrast with in the energy-dependent images is compared to known x-ray attenuation coeff icients of soft tissue (e.g. muscle, bone, and fat).