Frequency-Dependent Contrast Enhancement for Conductive and Non-Conductive Materials in Electrical Impedance Tomography  
[PERSON] 1,2,t  
1 Laboratory of Laser Technology, Faculty of Applied Science, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City 72409, Vietnam; [EMAIL_ADDRESS] (Q.T.N.D. ); [EMAIL_ADDRESS] (H.N.H. ); [EMAIL_ADDRESS] (M.Q.C.D. ); [EMAIL_ADDRESS] (T.V.H.) [PERSON]  
1 Laboratory of Laser Technology, Faculty of Applied Science, Ho Chi Minh City University of Technology (HCMUT), 268 Ly Thuong Kiet Street, District 10, Ho Chi Minh City 72409, Vietnam; [EMAIL_ADDRESS] (Q.T.N.D. ); [EMAIL_ADDRESS] (H.N.H. ); [EMAIL_ADDRESS] (M.Q.C.D. ); [EMAIL_ADDRESS] (T.V.H.) 2  
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The capability of EIT to reconstruct images based on an object's impedance distribution poses unique challenges and opportunities, particularly in differentiating materials with distinct electrical properties. Conductive materials, such as metals, saline solutions, or blood, permit the easy passage of electric currents, whereas non-conductive materials, such as plastics, resins, or air, resist electric currents. The frequency of the applied electric current is pivotal in determining how materials exhibit conductive or non-conductive characteristics. Spanning across the electromagnetic spectrum, from radio waves to gamma rays, frequency influences material responses, giving rise to the concept of frequency-dependent impedance. Impedance spectroscopy, used to understand these responses, provides insight into the structure and function of materials. Previous research has focused mainly on post-reconstruction contrast enhancement using techniques such as quantitative phase imaging, multi-frequency approaches, diverse reconstruction algorithms, and artificial intelligence (machine learning and deep learning) [6; 7; 8; 9; 10; 11; 12; 13; 14; 15]. An often overlooked consideration is determining the appropriate frequency range for each type of material to enhance the initial contrast. This study addresses this gap by establishing an empirical frequency range for both conductive and non-conductive materials through systematic experiments and evaluation indices, to provide valuable references for enhancing contrast. The experimental design includes a comprehensive investigation of the frequency-dependent contrast behavior in EIT. The process carried out a series of experiments with different materials, such as copper and acrylic resin, in various environments and configurations. The range of frequencies explored in these experiments was deliberately varied to observe how the contrast between materials changed with different excitation frequencies. The decision of what constitutes an \"empirical\" frequency range was based on a combination of analytical indices, including contrast, sharpness, and contrast-to-noise ratio (CNR). These indices were calculated from the reconstructed conductivity images obtained during the experiments. The goal was to identify frequency ranges in which these indices demonstrated favorable values, indicating enhanced contrast, resolution, and clarity in the EIT images. This study aimed to empirically determine frequency ranges that consistently provide desirable imaging outcomes across multiple experiments and conditions. This pragmatic approach aligns with the experimental nature of the study and the goal of providing practical insights into frequency-dependent contrast enhancement in EIT. The study delves into how different frequencies impact the contrast of conductive metals and non-conductive plastics in EIT images, employing principles from electromagnetic theory and impedance spectroscopy. The study objectives encompass:  
* Determining low-, medium-, and high-frequency ranges that enhance or diminish the contrast of metals and plastics in EIT images.