Improving Mammographic Density Estimation in the Breast Periphery

Xin Chen, Emmanouil Moschidis, Christopher Taylor, Susan Astley

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Mammographic density is a strong risk factor for breast cancer. Volumetric breast density can be estimated from a digital mammogram by modelling the imaging process; this provides a more accurate assessment than subjective and 2D area-based methods. However, reliable density estimation in the uncompressed peripheral breast region and determination of compression paddle tilt are still open and challenging problems that affect the accuracy of measurement. Here we present a complete system that is able to perform thickness correction for both the compressed and uncompressed breast regions. The system was evaluated on a dataset of 208 mammograms, and compared with results from commercial software VolparaTM (version 1.5). The proposed method yielded Pearson correlation coefficients (PCC) of volumetric breast density (VBD) between left and right breasts of 0.88 (CC view) and 0.91 (MLO view). The PCC between VolparaTM VBD and our method is 0.93.
Original languageEnglish
Title of host publicationBreast imaging
Subtitle of host publication13th International Workshop, IWDM 2016, Malmö, Sweden, June 19-22, 2016, proceedings
EditorsAnders Tingberg, Kristina Lång, Pontus Timberg
PublisherSpringer Nature
ISBN (Print)978-3-319-41545-1
Publication statusPublished - 2016

Publication series

NameLecture Notes in Computer Science


  • Digital mammogram
  • Volumetric breast density
  • Thickness correction
  • Compression paddle tilt


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