Do we really need to recalibrate the CT system Configuration for every experiment?

TL;DR

This paper investigates how the density distribution of objects affects CT system configuration, emphasizing the need for on-spot customization of parameters like detector number and geometry without frequent recalibration.

Contribution

It introduces a simulation and experimental study on the influence of object density and detector count on CT configuration, highlighting the importance of adaptable setups.

Findings

Object density distribution impacts CT geometry parameters.

Simulation results align well with experimental data.

On-spot customization can optimize CT system performance.

Abstract

Different technical and physical factors may affect the image quality reconstructed using a Computed Tomography system. We have developed and designed a 2D Gamma Computed Tomography set up to study the effect of some physical parameters. One must decide the number of detectors and set CT geometry parameters or configuration like the fan-beam angle and number of rotations. Usually, geometry parameters are determined based on the objects size. This study shows the influence of the density distribution of same-sized phantom or objects on CT geometry parameters. Due to limited space, industrial applications may not allow a CT system to move around the object (under investigation). On-spot customization of CT system configuration may be required according to similar situations. The same problem is experienced in medical science, material science, and many other fields in which the CT system is widely used for non-destructive imaging. The number of detectors in the scanning array is one major factor that optimizes a CT system. Of course, more detectors are desired for better resolution. Changing the number of detectors requires recalibration of CT geometry. A simulated work is presented to study the influence of the density distribution of same-sized objects and the number of detectors on CT system configuration. The same is verified experimentally also. A comparison between simulated and experimental results shows a good agreement.