Finding cancer in mammograms: if you know it’s there, do you know where?

Ann Carrigan, Susan Wardle, Anina N Rich

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)
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Humans can extract considerable information from scenes, even when these are presented extremely quickly. The ability of an experienced radiologist to rapidly detect an abnormality on a mammogram may build upon this general capacity. Although radiologists have been shown to be able to detect an abnormality ‘above chance’ at short durations, the extent to which abnormalities can be localised at brief presentations is less clear. Extending previous work, we presented radiologists with unilateral mammograms, 50% containing a mass, for 250 or 1000 ms. As the female breast varies with respect to the level of normal fibroglandular tissue, the images were categorised into high and low density (50% of each), resulting in difficult and easy searches, respectively. Participants were asked to decide whether there was an abnormality (detection) and then to locate the mass on a blank outline of the mammogram (localisation). We found both detection and localisation information for all conditions. Although there may be a dissociation between detection and localisation on a small proportion of trials, we find a number of factors that lead to the underestimation of localisation including stimulus variability, response imprecision and participant guesses. We emphasise the importance of taking these factors into account when interpreting results. The effect of density on detection and localisation highlights the importance of considering breast density in medical screening.
Original languageEnglish
Article number10
Pages (from-to)1-14
Number of pages14
JournalCognitive Research: Principles and Implications
Publication statusPublished - 18 Apr 2018

Bibliographical note

Copyright the Author(s) 2018. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • visual search
  • medical imaging
  • global processing
  • breast density
  • target detection
  • target localisation


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