  Dual-energy computed tomography (DECT) is a promising technology that has
shown a number of clinical advantages over conventional X-ray CT, such as
improved material identification, artifact suppression, etc. For proton therapy
treatment planning, besides material-selective images, maps of effective atomic
number (Z) and relative electron density to that of water ($\rho_e$) can also
be achieved and further employed to improve stopping power ratio accuracy and
reduce range uncertainty. In this work, we propose a one-step iterative
estimation method, which employs multi-domain gradient $L_0$-norm minimization,
for Z and $\rho_e$ maps reconstruction. The algorithm was implemented on GPU to
accelerate the predictive procedure and to support potential real-time adaptive
treatment planning. The performance of the proposed method is demonstrated via
both phantom and patient studies.
