Breast cancer is one of the most common malignancies in women and it continues to be a major cause of death among women worldwide. Several studies have shown that the women with dense breasts are at higher risk than the women whose breasts are less dense. Hence, breast density has to be accepted as a clinically highly significant predictor of breast cancer risk. Most studies of breast density are performed on the mammographic images. Because the two-dimensional (2-D) mammographic density shows large variability, the three-dimension (3-D) breast magnetic resonance imaging (MRI) has been used in some recent studies for achieving more reasonable consistency. Recently, a new technique, 3-D automatic breast ultrasound (ABUS) has been developed to acquire the whole breast images. The densities computed from the images of three different modalities, mammography, MRI, and ABUS, for the same patient will be compared in this paper. In order to analyze these three kinds of medical images, three different segmentation methods are used to find the breast region. Moreover, the fuzzy c-mean (FCM) classifier is used to analyze the breast densities of 3-D breast MRI and ABUS images. The experiments of 67 breasts from 40 patients show that the mammographic, ABUS, and breast MRI densities have high positive correlation and all of them could provide the useful breast density information to physician. The correlation factor R2 of linear regression between mammographic and breast MRI images is up to 0.932. The correlation factor R2 between mammographic and ABUS images is 0.669 and the correlation factor R2 between breast MRI and ABUS images is 0.760.