Analysis and evaluation of tomographic gamma scanning image reconstruction algorithm

Abstract

Tomographic Gamma Scanning (TGS) is a nondestructive analysis technique for accurately measuring the content of radioactive material in sealed containers. It has important applications in the fields of nuclear safety assurance and the measurement and analysis of radioactive waste drums. As the key of TGS technique, the quality of the emission image reconstruction algorithm will directly affect the accuracy of measurement results. In this paper, a computer simulation platform for TGS technique is established. The application of four emission image reconstruction algorithms in TGS technique is systematically studied by using 6 6 6 sample voxel model. Three representative sample media and radioactive source distribution models are established and the applicability of the four reconstruction algorithms is analyzed and evaluated in the presence and absence of detector noise interference. Computer simulation and experimental results show that ML-EM algorithm is the most applicable in the process of TGS image reconstruction.