  One of the advantages of spectral computed tomography (CT) is it can achieve
accurate material components using the material decomposition methods. The
image-based material decomposition is a common method to obtain specific
material components, and it can be divided into two steps: image reconstruction
and post material decomposition. To obtain accurate material maps, the image
reconstruction method mainly focuses on improving image quality by
incorporating regularization priors. Very recently, the regularization priors
are introduced into the post material decomposition procedure in the iterative
image-based methods. Since the regularization priors can be incorporated into
image reconstruction and post image-domain material decomposition, the
performance of regularization by combining these two cases is still an open
problem. To realize this goal, the material accuracy from those steps are first
analyzed and compared. Then, to further improve the accuracy of decomposition
materials, a two-step regularization based method is developed by incorporating
priors into image reconstruction and post material decomposition. Both
numerical simulation and preclinical mouse experiments are performed to
demonstrate the advantages of the two-step regularization based method in
improving material accuracy.
