Abstract

Info

Title:: An adaptive total p variation-constrained CT image reconstruction method for limited angle data

Author(s):: LI Huijun; WANG Linjing; ZHOU Lu; PENG Yingying; ZHANG Shuxu; Radiation Therapy Center, Cancer Center of Guangzhou Medical University, Guangzhou 510095, China

Keywords:: ; limited angle; computed tomography; image reconstruction; total variation; adaptive total p variation; iterative algorithm

Abstract:: An improved algebraic iterative reconstruction algorithm based on the total p variation (TpV) was proposed for the reconstruction of CT images with limited projection angles. Two-phase reconstruction structure was applied in the improved algorithm. The algebraic reconstruction technique was firstly adopted to reconstruct image that meet the identity of projection data and applied to correct non-negativity. Subsequently, adaptive TpV regularization was used to constrain the image sparse features, further optimizing the reconstruction results, in which the parameter p was adjusted according to the image region characteristics. Two phases alternated with each other until meeting the convergence criteria. The classical Shepp-Logan phantom was applied to perform a simulation reconstruction for the improved algorithm. The reconstructed images and its local zoom-in views were used for subjective analysis, while the profile graphs and the normalized absolute distance were regarded as the objective evaluation criterions. The results demonstrated that compared with the images reconstructed by conventional algebraic reconstruction technique-total variation algorithm, the images reconstructed with the improved algorithm were not only close to the real Shepp-Logan phantom with smaller reconstruction errors, but also achieve a better protection for the edge features of images.