Brest cancer as the most common cancer in women, is a leading cause of cancer death in the Western world. Breast density is defined by the amount of fibroglandular tissue (FGT) relative to fatty components within the breast and has been shown to be a recognized and independent risk factor for breast cancer. The American College of Radiology (ACR) recommends the assessment of breast composition on mammography, a two-dimensional technique and the current recommended screening method for breast cancer, according to the four, well-established subjective density categories of the Breast Imaging Reporting and Data System (BI-RADS). However, research has shown that this assessment is liable to create poor intra- and interobserver variability, with a lack of consistency. Therefore, it would be preferable to perform an automated and quantitative assessment of breast density based on a threedimensional method. Our results show that an automated, user-independent, quantitative measurement of the amount of FGT with MR imaging, based on the Dixon sequence, is a feasible tool, with which a robust and reproducible, as well as radiation- and compression-free measurement of FGT is possible. Furthermore, we proved the superiority of Dixon-type sequences with regard to the sequence protocol and precision of measurements when compared to known breast compositions. In our studies, automated volumetric measurements of FGT with MR imaging showed feasibility, robustness, and applicability on different MR units. In addition, we demonstrated considerable differences in repeated, subjective visual estimates of the amount of FGT with MR imaging, which also showed significant deficits compared to automated, quantitative measurement for a reliable and standardized assessment of FGT with MR imaging. Automated, three-dimensional breast density measurements with MR imaging is possible and yields reproducible outcomes even at different spatial resolutions, therefore, it is recommended as the standard of reference in the assessment as imaging biomarker.