Breast cancer continues to be a leading cause of death in Western countries. One of the most important approaches to reduce this mortality is to detect the cancer as early as possible. Although current diagnostic imaging modalities are able to give useful information for diagnosis, development of new imaging technique is highly desirable in order to detect breast cancer in an earlier stage. This is the motive of the present study of Electrical Impedance Mammography (ElM), which applies Electrical Impedance Tomography (EIT) to image human breasts. The overall aim of the whole project is to develop impedance imaging techniques and system for early detection of breast cancer. The aim of the studies reported in this thesis is twofold, to investigate methods of improving EIT image quality and the feasibility of EIT in breast cancer detection. Focusing on these aims the following work is reported: 1) The study of three different image reconstruction algorithms is described. In this work the image reconstruction results are compared and the most appropriate algorithm was chosen for the subsequent study of breast imaging. 2) An investigation of two important factors in EIT image reconstruction, the number of electrodes (NOE) and the number of conductivity basis functions (NOCBF) whose effects on EIT images have yet been studied in detail so far, are described. In this work the image reconstruction is analysed with different combinations of NOE and NOCBF using Singular Value Decomposition (SVD) and spectrum expansion theory. Finally suggestions are given on which configuration could offer better image quality in breast imaging3) A comprehensive investigation is reported regarding compatibility of different types of prior information and its effect on an iterative image reconstruction algorithm, based on which a novel method is proposed to improve EIT image quality. This method selects compatible prior information by observing the convergence behaviour of an image reconstruction algorithm. The principle, implementation, and results are detailed. Results indicate the effectiveness of this method. 4) A two-dimensional breast imaging simulation system is introduced. In this work several breast models with different physiological and pathological conditions are made, based on clinical in vitro measurements and Cole-Cole model. Images with different current frequencies are reconstructed and analysed. Results indicate the potential of detecting and identifying breast abnormality by EIT. 5) A preliminary study on 3D EIT and 3D electrode placement has been conducted. The mathematic principle and implementation of 3D EIT are described, followed by a study on the sensitivity of boundary measurements to the conductivity changes in a cylindrical object with 2 different types of electrode placement. Suggestions are given on optimal electrode placement in EIT breast imaging. Finally suggestions are gIven for future work. These include a) investigating appropriate electrode placement for different applications and corresponding current & voltage patterns; b) incorporating more prior information into ElM image reconstruction; c) designing a more precise 3D breast forward model; and d) investigating appropriate regularization for image reconstruction