Two-dimensional electrical impedance tomography (EIT) for characterization of body tissue using a gauss-newton algorithm

The gauss-newton algorithm is applied to reconstruct a two-dimensional image of Electrical Impedance Tomography (EIT) using python program. The study aimed to determine the characteristics of body tissues either conductive or resistive properties through the tissue structure which is displayed in the form of images so we can distinguish between one tissue and another. In this study, it was a fabricated hardware system, phantom, and software system. The EIT technique is performed by injecting a low constant electrical current of 1 mA at 50 kHz frequency on a pair of electrodes on 16 copper electrodes (Cu) surrounding a phantom filled with ground meat as conductor of electricity, flat bone, and cord bone of chicken as anomalies. The principle of the neighboring method achieved voltage measurements from the other electrode pair. The measurement data is processed with the python program using gauss-newton algorithm to obtain a reconstructed image of the tissue structure. The characteristics of body tissue can be identified from the color distribution, position, shape, and size of the object in the reconstructed image so it can distinguish between one tissue and another. The original analysis of body tissue either conductive or resistive properties could be reconstructed by two-dimensional electrical impedance tomography conjunction with the gauss-newton algorithm.