July 2013
Volume 13, Issue 9
Vision Sciences Society Annual Meeting Abstract  |   July 2013
Adaptation and visual search in medical images
Author Affiliations
  • Elysse Kompaniez
    Psychology, University of Nevada, Reno
  • Criag K. Abbey
    Psychology, University of California, Santa Barbara\nRadiology, University of California, Davis
  • John M. Boone
    Radiology, University of California, Davis\nBiomedical Engineering, University of California, Davis
  • Michael A. Webster
    Psychology, University of Nevada, Reno
Journal of Vision July 2013, Vol.13, 1232. doi:https://doi.org/10.1167/13.9.1232
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      Elysse Kompaniez, Criag K. Abbey, John M. Boone, Michael A. Webster; Adaptation and visual search in medical images. Journal of Vision 2013;13(9):1232. https://doi.org/10.1167/13.9.1232.

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

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Radiologists face the visually challenging task of detecting suspicious features within the complex and noisy backgrounds characteristic of medical images. We used a search task to examine whether salience of target features in x-ray mammograms could be enhanced by prior adaptation to the spatial structure of the images. Stimuli were 6.6 by 8.75 deg randomly selected sections from normal mammograms previously classified with BIRADS Density scores of "fatty" vs. "dense," corresponding to differences in the relative quantities of fat vs. fibroglandular tissue. The categories reflect large differences in visual texture with dense tissue appearing cloudier and more likely to obscure lesion detection. Targets were simulated tumors corresponding to bright Gaussian spots (sd = .18 deg), superimposed by adding the luminance to the background. A single target was added to each image at random locations, with contrast varied over 5 levels so that they varied from difficult to easy to detect. Reaction times were measured for detecting the target location (left or right side), before or after adapting to a gray field or random sequences of a different set of dense or fatty images (shown 4/sec for 5 min initial adapt and then 4 sec prior to each test). Observers were faster at detecting the targets in dense images after adapting to the dense structure, compared to performance for the same stimuli when instead adapted to the gray field. In contrast, adaptation to fatty images did not consistently improve reaction times. These differences could reflect differences in the relative clutter and contrast of the two image categories. For dense images, our results suggest that visual salience and search efficiency could be heightened when observers are adapted to the backgrounds they are searching on, perhaps because this adaptation allows observers to more effectively suppress the structure of the background.

Meeting abstract presented at VSS 2013


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