December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Serial Dependence in Radiologist Perception across Naturalistic Mammogram Stimuli
Author Affiliations & Notes
  • Zhihang Ren
    University of California, Berkeley
  • Teresa Canas-Bajo
    University of California, Berkeley
  • Min Zhou
    The First People's Hospital of Shuangliu District, Chengdu, China
  • Stella X. Yu
    University of California, Berkeley
  • David Whitney
    University of California, Berkeley
  • Footnotes
    Acknowledgements  This work has been supported by National Institutes of Health (NIH) under grant #R01CA236793.
Journal of Vision December 2022, Vol.22, 3835. doi:
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      Zhihang Ren, Teresa Canas-Bajo, Min Zhou, Stella X. Yu, David Whitney; Serial Dependence in Radiologist Perception across Naturalistic Mammogram Stimuli. Journal of Vision 2022;22(14):3835.

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      © ARVO (1962-2015); The Authors (2016-present)

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Radiologists rely on visual perception to diagnose breast diseases via mammograms. A basic underlying assumption in medical image perception is that clinician visual perception and decision at any moment is largely independent of recently seen radiographs; however, that may not be true. Researchers have found that serial dependence, the tendency for the visual system to bias representations toward recent history, occurs more frequently between ambiguous stimuli just like those found in radiological screening (Cicchini, et al., 2014; Fischer & Whitney, 2014; Liberman et al., 2014; Kiyonaga et al., 2017). In particular, recent work shows that radiologist perception of simulated tumors is biased toward previously seen stimuli (Manassi et al., 2019; Ghirardo et. al., 2020). However, previous work was limited to unrealistic stimuli. To address the limitation, a generative adversarial network was developed to produce naturalistic mammogram stimuli (Ren et al., 2020). In this study, we aimed to investigate if radiologists also experience serial dependence with these realistic stimuli. In each trial, radiologists viewed a random simulated mammogram and subsequently matched the mammogram by picking the image from a morph continuum. The reported mammograms were pulled 9% towards those seen in the previous trials. These findings suggest that serial dependence extends to realistic radiographs and that it occurs even for radiologists. Serial dependence could therefore have a negative impact on the diagnostic accuracy of practicing clinicians.


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