Prostate MRI is becoming an increasingly popular imaging technique for the detection of prostate cancer. However, it requires a substantial amount of expertise and time from radiologists to accurately report on prostate MRI. Furthermore, quantitative analysis is needed for accurate assessment of cancer aggressiveness in vivo. Computer-aided detection and diagnosis (CAD) systems are excellent tools to tackle these challenges. In this thesis the design of such a systems is discussed. CAD systems are typically a connected pipeline of differing algorithms performing consecutive tasks, for example segmentation, feature extraction and classification. We followed a similar outline in this thesis. In Chapter 2 we discuss the segmentation of the prostate capsule in the setting of a ‘grand challenge’. Further division of the prostate capsule in distinct anatomical zones is the topic of Chapter 3. After segmentation of the capsule and the prostate zones, features discriminative for cancer and cancer aggression are discussed in Chapter 4 and 5. The interconnection of the components into one unified CAD system is subsequently discussed in Chapter 6 and the evaluation of the system in a clinical setting in Chapter 7. In this last Chapter we not only show that designing a fully automated CAD system is feasbile, but that it can be used to the benefit of radiologists.