A local reconstruction method for low-energy gamma-ray computed tomography system

In the application of computed tomography (CT) system to industrial multiphase flow visualization, the number of projections is usually limited, and the detector elements are sparsely arranged, the limited number of measurement data has put the validity of the conventional reconstruction algorithms in jeopardy. Although improved iterative reconstruction methods have been developed to compensate for the lack of projection data, the imaging quality is still inadequate for the reconstruction of relatively complicated flow regime. To overcome this problem, we propose a novel local reconstruction method based on the Landweber algorithm and apply it to a low-energy gamma-ray CT system for two-phase flow measurement. The object to be reconstructed is partitioned into a number of sub-regions and local reconstruction is implemented on each sub-region utilizing only gamma-rays passing through that region. The feasibility is demonstrated in both numerical simulations and prototype experiments. Comparison between the proposed method and the Landweber iterative algorithm shows that the former has obviously improved the imaging quality.