This thesis consists of three sections, the first two deal with the development and testing of an electrical impedance tomography prototype system for imaging breast cancer. The third section sues mutlivariate statistical methods to improve EIT image quality. The McMaster EIT System Mk1.0 is the resultant system of the system development. The EIT system is a 48 electrode, single current source, serial acquisition device with an operational frequency between 100Hz to 125kHz. The device is able to inject current between any two electrodes and is able to perform single or differential measurements on any two electrode pairs. The system is equipped with a virtual phase-lock loop and is capable of paramatic imaging. The system was tested using tests common to most electrical devices and specifically designed for EIT systems, to both benchmark the system and detect any errors. The testing revealed the device while able to produce viable EIT images; system suffers from a large stray capacitance. Due to stray capacitance the system injection amplitude accuracy varies with frequency and load. The system SNR is over 100dB with a 125kHz signal with a 5mA signal and compares favourably with existing EIT systems. The CMRR of the system closely tracked the published CMRR of the underlying commercial components and is comparable to existing systems. A second source of error which needs to be rectified in future deigns is the high contact impedence; which causes high direct current offset. Multivariate testing was used to detect errors which could not be easily discovered using conventional testing. The testing, performed iteratively detected several electronic errors which were fixed during development of the device. Six related models were developed for system noise, each with a different set of underlying assumptions about the source of noise. Of the models only one model proved to be a success on both qualitative and quantitative analysis of sample data sets. Finally an alternate model to the Cole-Cole parametric imaging based on PCA was proposed. The model proved to be better at modeling the underlying tissue variations in the presence of noise than Cole-Cole based models. The prototype EIT system presented in this thesis is a viable EIT system, but is in need of improvements to shielding to improve system performance. Also in need of improvement is the operational frequency and modifications toward a distributed architecture. The multivariate methods used for modelling system noise and tissue should be combined into one method for maximum benefit. / Thesis / Master of Applied Science (MASc)