In electrical impedance tomography (EIT), distribution of the internal resistivity or conductivity of an unknown object is estimated using measured boundary voltage data induced by different current patterns with various reconstruction algorithms. The reconstruction algorithms usually employ the Newton-Raphson iteration scheme to visualize the resistivity distribution inside the object. Accuracy of the imaging process depends not only on the algorithm used, but also on the scheme of finite element discretization. In this paper an adaptive mesh refinement is used in a modified reconstruction algorithm for the regularized EIT. The method has a major impact on efficient solution of the forward problem as well as on achieving improved image resolution. Computer simulations indicate that the Newton-Raphson reconstruction algorithm for EIT using adaptive mesh refinement performs better than the classical Newton-Raphson algorithm in terms of reconstructed image resolution. In electrical impedance tomography (EIT), distribution of the internal resistivity or conductivity of an unknown object is estimated using measured boundary voltage data by different current patterns with various reconstruction algorithms. The reconstruction algorithms usually employ the Newton-Raphson iteration scheme to visualize the resistivity distribution inside the object. Accuracy of the imaging process depends not only on the algorithm used, but also on the scheme of finite element discretization. In this paper an adaptive mesh refinement is used in a modified reconstruction algorithm for the regularized EIT. The method has a major impact on efficient solution of the forward problem as well as on achieving improved image resolution. Computer simulations indicate that the Newton-Raphson reconstruction algorithm for EIT using adaptive mesh refinement perform better than the classical Newton-Raphson algorithm in terms of reconstructed image resolution.