Discriminative feature representation to improve projection data inconsistency for low dose CT Imaging

In low dose computed tomography (LDCT) imaging, the data inconsistency of measured noisy projections can significantly deteriorate reconstruction images. To deal with this problem, we propose here a new sinogram restoration approach, the sinogram-discriminative feature representation (S-DFR)method. Different fromother sinogram restorationmethods, the proposedmethod works through a 3-D representation-based feature decomposition of the projected attenuation component and the noise component using awell-designedcomposite dictionary containing atoms with discriminative features. This method can be easily implemented with good robustness in parameter setting. Its comparisonto othercompetingmethods through experiments on simulated and real data demonstrated that the S-DFR method offers a sound alternative in LDCT.