Automated assessment of area of dense tissue in the breast: A comparison with human estimation

Camilla Jeffries-Chung, Jennifer Diffey, Michael Berks, Joanna Morrison, Rosanne Verow, Julie Morris, Mary Wilson, Caroline Boggis, Nicky Barr, Anthony Maxwell, Alan Hufton, Susan Astley

    Research output: Contribution to journalArticlepeer-review


    Both interactive thresholding tools and human visual assessment have been related to the risk of developing breast cancer. In this paper we explore the relationship between human assessment of area of dense tissue and the actual thickness of tissue in the breast by using a volumetric density technique to compute areas of dense tissue, varying the threshold below which areas of low density are discounted and observing the correlation with visual assessment of density at different thresholds. Based on analysis of thresholds used in the automated method, radiologists' definition of a dense pixel is one in which the percentage of glandular tissue is between 10% and 20% of the total thickness of the compressed breast at that point. © 2010 Springer-Verlag.
    Original languageEnglish
    Pages (from-to)168-174
    Number of pages6
    JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Publication statusPublished - 2010


    • breast density
    • computer analysis
    • human perception
    • risk assessment


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