Non-destructive Evaluation of Micro-scale Heterogeneity using High-frequency Ultrasound Scattering Analysis

Abstract

Ultrasound imaging is a widely used technique for monitoring internal structures in biomedical and industrial applications. In biomedical applications, ultrasound imaging is used to diagnose diseases by observing changes in the internal structure and physical properties of tissues. For industrial applications, ultrasound imaging primarily uses non- destructive testing, which enhances production effectiveness. Beyond simple structural recognition, there is an increasing demand for functional ultrasound techniques to obtain more detailed information. For example, changes in the physical properties of micro-scaled objects are significant in biomedical and industrial applications. To address this need, we propose ultrasound scattering analysis using a high-resolution ultrasound imaging system. Initially, we developed the ultrasound imaging system and various ultrasound probes, including multiple operating frequency bands and path-type ultrasound probes. Additionally, we developed a portable ultrasound imaging system and ultimately built a high-resolution ultrasound imaging system. We fabricated steel sheet samples with high- and low-density scatterers for speckle analysis. Various types, sizes, and concentrations of scatterers were used to prepare pipeline samples. Our results showed that our speckle analysis method could distinguish scatterers based on their properties, with significant differences observed. We analyzed the number and size distributions of the speckles to distinguish the scatterers statistically. Further experiments were conducted to verify the applicability of our method, and a simple deep-learning model was also applied to enhance our analysis. Through this study, we demonstrated that speckle analysis using high-resolution ultrasound images can quantify the properties of micro-scaled objects and distinguish them. The proposed method is a novel approach to analyzing ultrasound scattering signals and represents a significant step towards acquiring detailed information beyond simple structural analysis, serving as a leading indicator for various purposes.