  This work considers synergistic multi-spectral CT reconstruction where
information from all available energy channels is combined to improve the
reconstruction of each individual channel, we propose to fuse this available
data (represented by a single sinogram) to obtain a polyenergetic image which
keeps structural information shared by the energy channels with increased
signal-to-noise-ratio. This new image is used as prior information during a
channel-by-channel minimization process through the directional total
variation. We analyze the use of directional total variation within variational
regularization and iterative regularization. Our numerical results on simulated
and experimental data show improvements in terms of image quality and in
computational speed.
