Breast cancer is the most common type of cancer and the 5th leading cause of death amongst women in developed countries as of 2004, according to the World Health Organisation. X-Ray mammography is the defacto imaging examination used for diagnosis; however there are well-known limitations in terms of sensitivity and specificity, especially in dense breasts common in younger women. This leads to worrying levels of false results, which may ultimately compromise the efficiency of treatment.This project will combine two novel breast cancer imaging techniques: Positron Emission Mammography (PEM) and Ultra Wideband Radar (UWB). It is sought to create equivalent computer breast and tumour models that will be used simultaneously in PEM and UWB simulations. This will be accomplished by adapting Magnetic Resonance breast data, in collaboration with the University of Calgary, Canada. Different types of tissue will be modelled in an FDTD simulation for UWB, while Monte Carlo simulations will be used for PEM. We will use simulated data to test the sensitivity and specificity of detection and classification of tumours, varying from very fatty to high dense breast models.Doubtful classification of tumours that may be obtained with PEM (in cases of small multifocal tumours or in cases with borderline Standardized Uptake Values) are expected to be resolved by applying combined automatic classification techniques to Radar Target Signatures of tumours obtained with UWB. The use of radar information will help differentiate tumours fine morphology (invisible to PEM) increasing the knowledge about its aggressiveness.The main objective of this work is to make a significant contribution to a more reliable multimodal breast examination which will have higher rates of sensitivity and specificity. In view of recent technical developments in UWB Radar and PEM systems, we aim to provide the basic scientific knowledge to justify the interest of building a hybrid PEM-UWB system.