Abstract
Electrical Impedance Tomography (EIT) is a non-invasive imaging technique that displays changes in conductivity within a body. This method finds application in biomedical and geology. EIT finds use in medical applications, as the different tissues of the body have different conductivity and dielectric constants. In this paper a phantom model is designed considering Finite Element Model (FEM). AC current of amplitude 1 mA and frequency 1 KHz is applied considering adjacent protocol with noise less and noisy cases. From the computed voltage data image is reconstructed using Kalman algorithm. For noisy case noise levels equal to Signal-to-Noise Ratio (SNR) 30 dB, 15 dB and 7 dB were considered. Kalman algorithm is studied for EIT image reconstruction in noise free and noisy case, in terms of shape, size, spatial location of the target object.
Highlights
Non-destructive imaging systems have experienced a great technological development in last few decades, allowing the evolution from planar image to full 3-D reconstructions, from static images to dynamic and functional ones
The basic principle of this method is the repeated measurement of surface voltages of a body, which are a result of rolling injection of known and small-volume sinusoidal AC current to the body through the electrodes attached to its surface and reconstructing conductivity images from the measured data [1]
To find the electrical impedance distribution within the volume researches developed different types of reconstruction algorithms. Among those followings are most widely used such as Back-Projection (BP) algorithm, Filtered Back-Projection (FBP) algorithm, Gauss-Newton (GN) algorithm, Kalman algorithm and Total Variation (TV) regularized Primal Dual-Interior Point Methods (PDIPM) algorithm [22]
Summary
Non-destructive imaging systems have experienced a great technological development in last few decades, allowing the evolution from planar image to full 3-D reconstructions, from static images to dynamic and functional ones. It is a growing field, with each year bringing new imaging systems, improvement of older ones, new numerical techniques, all of them with a wide spectrum of applications, making it a very interesting and appealing area of knowledge [2]. The electrical properties of human body tissues made it possible to reconstruct the conductivity images and retrieving the information of the interior of the body
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