We applied the multiplicative regularization scheme to the image reconstruction of electrical impedance tomography (EIT) to alleviate its ill-posedness. In this scheme, an objective function is constructed in which the data misfit function is multiplied by a regularization function. The main advantage of this scheme over the additive regularization scheme is that no artificial regularization parameter needs to be set in the objective function. Based on the multiplicative scheme, we formulated both the absolute and difference image reconstruction problems. Numerical and experimental results show the promising application of this scheme for thoracic imaging.