The project PROSTATE aims to design and implement a system for automated staging of prostate cancer using magnetic resonance imaging modalities. Staging of prostate cancer is performed mainly by radiologists and their decision is influenced by the findings on MR images of the prostate and the clinical results. MR images are currently the best technique to assess problems associated with soft tissues and are offering a non-invasive solution for obtaining accurate morphologic, dynamic contrast enhanced (DCE) and spectroscopy images. As opposed to the examination of the MRI evidence with the naked eye, the current frame of work offers an automated classification of the several stages of the disease. The extracted MRI features as well as the clinical data of patients are correlated through Data fusion schemes to provide a set of training data for the classification algorithms. Finally, classification is achieved through the training of the system with a number of cases that will result in specific recognition of patterns which will be used for the classification of the prostate cancer stages.