Evaluation of iterative algorithms for tomograhy image reconstruction – a study using a third generation insdutrial tomography system

Abstract

The greatest impact of the tomography technology currently occurs in medicine. The success is due to the human body presents standardized dimensions with well-established composition. These conditions are not found in industrial objects. In industry, there is much interest in using the tomography in order to know the inner of (i) the manufactured industrial objects or (ii) the machines and their means of production. In these cases, the purpose of the tomography is to (a) control the quality of the final product and (b) to optimize production, contributing to the pilot phase of the projects and analyzing the quality of the means of production. This scan system is a non-destructive, efficient and fast method for providing sectional images of industrial objects and is able to show the dynamic processes and the dispersion of the materials structures within these objects. In this context, it is important that the reconstructed image presents a great spatial resolution with a satisfactory temporal resolution. Thus the algorithm to reconstruct the images has to meet these requirements. This work consists in the analysis of three different iterative algorithm methods, such Maximum Likelihood Estimation Method (MLEM), Maximum Likelihood Transmitted Method (MLTR) and Simultaneous Iterative Reconstruction Method (SIRT. The analysis consists on measurement of the contrast to noise ratio (CNR), the root mean square error (RMSE) and the Modulation Transfer Function (MTF), to know which algorithm fits better the conditions in order to optimize system. The algorithms and the image quality analysis were performed by the Matlab® 2013b.