Investigating the effect of data acquisition geometry and image reconstruction method on neutron computed tomography images at Tehran Research Reactor

Neutron Computed Tomography (nCT) is one of the modern applications of research reactors. The combination of the Three-dimensional representation capability of tomographic imaging and the unique properties of neutron interaction with materials creates valuable information about the internal structure of materials and components. In this study, the effect of data acquisition geometry and method of image reconstruction on tomographic images of the Tehran Research Reactor Imaging Facility (TRRIF) have been investigated based on contrast and the ratio of contrast to noise parameters. In experimental data acquisition, two radiation geometries have been aligned with angular steps of 1 and 0.5 degrees, respectively. Two samples were turned within the neutron radiation field at a half-screen. Image reconstruction has been performed through FBP and ART, SART, and SIRT algorithms, using Python programming language. The stack of images has been rendered to gain sample volume. Initially, in order to reconstruct the image through a high-quality set of projections, experimental data acquisition parameters have been optimized. Then, pre-processing has been carried out on projections. The results showed that the sample components and some defects could be differentiated from each other. Contrast and CNR were improved in data acquisition geometry with smaller angular steps and through SIRT reconstruction method.