Development of image reconstruction for Gamma-ray CT of large-dimension industrial plants using Monte Carlo simulation

Abstract

In industrial Gamma-ray CT, specifically for large-dimension plants or processes, the simplicity and portability of CT system necessitate to use individual gamma-ray detectors for imaging purposes. Considering properties of the gamma-ray source as well as characteristics of the detectors, including penetration depth, energy resolution, size, etc., the quality of reconstructed images is limited. Therefore, implementation of an appropriate reconstruction procedure is important to improve the image quality. In this paper, an accurate and applicable procedure has been proposed for image reconstruction of Gamma-ray CT of large-dimension industrial plants. Additionally, a portable configuration of tomographic system was introduced and simulated in MCNPX Monte Carlo code. The simulation results were validated through comparison with the experimental results reported in the literature. Evaluations showed that maximum difference between reconstruction error in this work and the benchmark was less than 1.3%. Additional investigation has been carried out on a typical standard phantom introduced by IAEA using the validated procedure. Image quality assessment showed that the reconstruction error was less than 1.7% using different algorithms and a good contrast higher than 76% was obtained. Our overall results are indicative of the fact that the procedures and methods introduced in this work are quite efficient for improving the image quality of gamma CT of industrial plants.