-In this paper we describe some software for image reconstruction of electric impedance tomography (EIT) made on Sharif University of Technology named (SUT-1). We will discuss about image reconstruction methods and we will show the results of s imulation and real measurement from SUT-1 system.Keywords -Electrical Impedance Tomography, Image Reconstruction, Inverse Problem I. INTRODUCTIONSUT-1 is a 32 electrodes electrical impedance tomograph that was designed and fabricated in Sharif University of Technology. In Fig. 1. general view of this system was showed. Information about hardware and main specification of system and some results and also software for solving forward problem by FEM was introduced before [1,2,3,4,5]. The main objective of this paper is discussion about some image reconstruction methods for EIT; presenting some results from image reconstruction software based on such methods and verification of software with simulation and actual test data from SUT-1. where ~( ) U P is voltage and ~( ) δ P is specific admittance of B; in which:S is surface boundary of B These equations are derived form of Maxwell s Equations with some approximation and an elliptic partial differential equation with Neumann boundary condition and with low frequency approximation of current injection in conductive media. As described above for solving this equation in forward problem FEM is used.2) Image Reconstruction Methods: Most important subject in EIT is its image reconstruction, because image reconstruction in EIT is an ill-posed inverse problem. From the time of advent EIT in 1983 very much works were made in EIT image reconstruction and this kind of effort is continued up to now. For reconstruction in mode of static imaging a modified NewtonRaphson Method with 32 electrodes was implemented. In this approach we interested in minimizing the function φ with respect to σ defined as follows:V is measured voltages and f is forwad problem results.The minimization of φ turns out to be the Newton iteration which is shown in this equation, This is simply an update for σ:For image reconstruction with this method some regularization needed [6]. And also sensitivity method used for image reconstruction. It uses a theorem derived by Geselowitz [7]. The theorem is best described using Fig. 2 Abstract Subject Terms Report Classification unclassified Classification of this page unclassified Classification of Abstract unclassified Limitation of Abstract UUNumber of Pages 4

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I certify that I have obtained a written permission from the copyright owner(s) to include the above published material(s) in my dissertation. I certify that the above material describes work completed during my registration as graduate student at the University of Windsor. I declare that, to the best of my knowledge, my dissertation does not infringe upon anyone's copyright nor violate any proprietary rights and that any ideas, techniques, quotations, or any other material from the work of other people included in my dissertation, published or otherwise, are fully acknowledged in accordance with I would like to take the opportunity at the beginning of this dissertation document to acknowledge those who played an important positive role in my doctoral studies journey. First and foremost, I would like to thank my PhD advisor, Dr. Ziad Kobti for his continuous support, kind and professional guidance during almost 5 years of my doctoral studies. His remarks and advises always illuminated the pathway to fulll one of my major dreams to get to this level of expertise.

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