Image gradient L0-norm based PICCS for swinging multi-source CT reconstruction

Dynamic computed tomography (CT) is usually employed to image motion objects, such as beating heart, corollary artery and cerebral perfusion. etc. Recently, to further improve the temporal resolution for aperiodic industrial process imaging, the swinging multi-source CT (SMCT) systems and the corresponding swinging multi-source prior image constrained compressed sensing (SM-PICCS) method were developed. Since the SM-PICCS uses the L-1-norm of image gradient, the edge structures in the reconstructed images are blurred and motion artifacts are still present. Inspired by the advantages in terms of image edge preservation and fine structure recovering, the L-0-norm of image gradient is incorporated into the prior image constrained compressed sensing, leading to an L-0-PICCS algorithm. The experimental results confirm that the L-0-PICCS outperforms the SM-PICCS in both visual inspection and quantitative analysis. 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement