All over the world, research groups are developing techniques in order to increase the probabilities of early detection of breast cancer, mainly by computer-aided diagnosis (CAD) schemes. However, dense breasts difficult many times this detection. In this type of breast, there are a larger amount of very absorbent tissues, so that the image contrast is decreased. This is an important constraint to the detection of suspicious structures, as, for example, clustered microcalcifications. Usually, dense breasts are characteristic of women less than 40 years old, and it is one of the reasons why tumors are detected in such women frequently only when they are already large, which difficults the treatment. Therefore, in this work we present the application of some image processing techniques intended to enhance the contrast in dense breast images, regarding the detection of clustered microcalcifications. The procedure was, firstly, determining in the literature the main techniques used for mammographic images contrast enhancement. The results indicate that, in general: (1) as expected, the overall performance of the CAD scheme for clusters detection decreased when applied exclusively to dense breast images, compared to the application to a set of images without this characteristic; (2) most of the techniques for contrast enhancement used successfully in generic mammography images databases are not able to enhance structures of interest in databases formed only by dense breasts images, due to the very poor contrast between microcalcifications, for example, and other tissues. These features should stress, therefore, the need of developing a methodology specifically for this type of images in order to provide better conditions to the detection of breast suspicious structures in these group of women.