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This study modifies a Tikhonov regularized "maximum a posteriori" algorithm proposed for reconstructing both the conductivity changes and electrode positioning variations in EIT and uses this algorithm for reconstructing images of 2d elliptical and square models, instead of simple circular model used in previous works. This algorithm had been proposed By C. Gomez for compensating the errors due to electrode movements in image reconstruction. The jacobian matrix has been constructed via perturbation both conductivity and electrode positioning. The prior image matrix should incorporate some kind of augmented inter-electrode positioning correlations to impose a smoothness constraint on both the conductivity change distribution and electrode movement. For each model, conductivity change image is reconstructed in 3 cases: a) With no electrode displacement using standard algorithm b) With electrode displacement using standard algorithm c) With electrode displacement using proposed algorithm. In all models, a comparison between 3 cases has been implemented. Also, the results obtained from each model have been compared with the other models in similar cases. The results obtained in this study will be useful to investigate the ellipticity effects of organs being imaged in clinical applications. Moreover, the effects of model deviation from circular form on reconstructed images can be used in special industrial applications.