Automatic characterization of breast density can enable more personalized breast cancer screening work flows. In this work, we present a novel method to automatically characterize breast density in mammography images. Our method computes a volumetric density map and measures the relative volume of glandular tissue VBD%. For critical cases when masking of small masses may be possible it additionally quantifies the masking effect of glandular tissue. VBD% and the masking risk combined provide a 4-point density score that correlates with the BI-RADS 5th edition guidelines. We evaluated our approach using a study with 32 radiologists and 2400 breast images 600 4-view FFDM exams. In a subset of 415 images identified as critical cases the accuracy to detect dense breasts density categories c or d increased as shown by the area under the curves 0.783 vs. 0.621. By taking masking risk into consideration our method provides a more comprehensive assessment of breast density.
['Andreas Fieselmann', 'Anna Jerebko', 'Thomas Mertelmeier']
Volumetric Breast Density Combined with Masking Risk: Enhanced Characterization of Breast Density from Mammography Images