Multi-Channel Trans-Admittance Imaging for Anomaly Detection

This research aims to develop an Electrical Impedance Tomography (EIT) system to detect anomalies in the network. The developed system utilizes 64 copper-based electrodes and Analog Discovery 2 as a real-time sinusoidal current source. The frequencies used are 50, 80, 100, 120, and 150 kHz because these frequency ranges are able to capture differences in network conductivity values. Each time data is captured, the system generates three main values, namely real, imaginary, and magnitude impedance values, each of which represents the conductivity conditions in the measurement area at 64 electrode points. The values are then converted into RGB format and mapped to be visualized in the form of an 8-bit digital image. In the reconstructed image, areas with significant differences in conductivity will appear with increasingly brownish shades of color, indicating a potential anomaly. The anomaly detection method in this study uses a 0.9% NaCl saline solution as the main medium. As a model of tissue anomalies, natural materials such as jicama and carrots are used. The anomaly position is varied at distances of 4 cm, 5 cm, 6 cm, and 7 cm, which is adjusted to the dimensions of the available acrylic containers to ensure systematic evaluation of the system against detection sensitivity at various depths. The results showed that the system was able to detect the difference in conductivity values between the anomaly and the anomalous area. Higher conductivity values are consistently measured in areas where anomalies are present compared to areas where there are no anomalies. The most optimal detection occurs at a measurement distance of 4 cm, as well as at the lowest frequency, which is 50 kHz.This method is an innovative solution for non-invasive and safe detection of tissue anomalies, without exposure to ionizing radiation, making it suitable for early diagnostic procedures in various medical fields, such as breast cancer detection, tumor identification, and other diagnostic applications. In addition, the system is low-cost and easy to use because the result is a visual image that makes it easy for medical personnel to interpret and analyze.