Estimation of breast density suffers from high inter-observer variability. A fully automated solution for objective and consistent assessment of breast density from full field digital mammography (FFDM) data is presented. For the computation of glandularity a region of interest (ROI) with a corresponding height model is automatically extracted from the mammograms. Assessment of adipose and glandular tissue volumes is performed by means of calibration data. Volumetric breast density is finally computed as the fraction of glandular tissue volume to overall breast volume with respect to the ROI. The fully automated approach provides volumetric breast density estimates that show strong non-linear correlation with the manual reference (R 2 =0.80) and high intra-patient consistency (R ∈[0.92,0.97]) among mammograms of different orientation or laterality. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Gooßen, A., Heese, H. S., & Erhard, K. (2012). Automatic volumetric glandularity assessment from full field digital mammograms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7361 LNCS, pp. 753–760). https://doi.org/10.1007/978-3-642-31271-7_97
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