Enhancing Low-Resolution Gamma Ray CT for Non-Invasive Inspection of Industrial Materials via ImageJ

Abstract Gamma-ray computed tomography (CT) offers unique advantages for non-invasive inspection of industrial materials, particularly in scenarios requiring high penetration. However, achieving high-resolution gamma-ray CT images can be challenging due to limitations in detector technology, radioactive source and data acquisition time. A series of low-resolution gamma-ray CT images of various industrial materials were acquired and analysed using Agensi Nuklear Malaysia’s gamma CT system. Despite inherent resolution constraints and significant data acquisition times, the system demonstrated a clear capability for detecting voids and discriminating between various material mixtures. This paper investigates the challenges associated with a low-resolution gamma-ray CT images and discusses results obtained during industrial material inspection. We present a computational methodology for addressing resolution limitations through image processing techniques and adapted analysis methods using ImageJ software. The results highlight ImageJ’s powerful functionalities in dealing with the limitations related to resolution, contrast and noise in gamma-ray CT imaging.