Breast density has been recognized as one of the major risk factors for breast cancer. However, breast density is currently estimated using mammograms which are intrinsically 2D in nature and cannot accurately represent the real breast anatomy. In this study, a novel technique for measuring breast density based on the segmentation of 3D cone beam CT (CBCT) images was developed and the results were compared to those obtained from 2D digital mammograms. 16 mastectomy breast specimens were imaged with a bench top flat-panel based CBCT system. The reconstructed 3D CT images were corrected for the cupping artifacts and then filtered to reduce the noise level, followed by using threshold-based segmentation to separate the dense tissue from the adipose tissue. For each breast specimen, volumes of the dense tissue structures and the entire breast were computed and used to calculate the volumetric breast density. BI-RADS categories were derived from the measured breast densities and compared with those estimated from conventional digital mammograms. The results show that in 10 of 16 cases the BI-RADS categories derived from the CBCT images were lower than those derived from the mammograms by one category. Thus, breasts considered as dense in mammographic examinations may not be considered as dense with the CBCT images. This result indicates that the relation between breast cancer risk and true (volumetric) breast density needs to be further investigated.