Positron Emission Tomography (PET) is a nuclear medicine technique that is being increasingly used for studying both the healthy brain and a variety of diseases. PET allows the in vivo estimate of physiological parameters such as blood flow, rate of glucose consumption and rate of tracer binding. When these parameters are estimated for each pixel of the image, parametric maps are generated. In this work Bayesian methodologies (population approaches and ridge regression) are studied for the improvement of the quality of PET parametric maps, with applications to several radioligands widely used...