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Proceedings Paper

Investigating the association of eye gaze pattern and diagnostic error in mammography
Author(s): Sophie Voisin; Frank Pinto; Songhua Xu; Garnetta Morin-Ducote; Kathy Hudson; Georgia D. Tourassi
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Paper Abstract

The objective of this study was to investigate the association between gaze patterns and the diagnostic performance of radiologists for the task of assessing the likelihood of malignancy of mammographic masses. Six radiologists (2 expert breast imagers and 4 Radiology residents of variable training) assessed the likelihood of malignancy of 40 biopsy-proven mammographic masses (20 malignant and 20 benign) on a computer monitor. Gaze data were collected using a commercial remote eye tracker. Upon reviewing each mass, the radiologists were asked to provide their assessment regarding the probability of malignancy of the depicted mass as well as a rating regarding the perceived difficulty of the diagnostic task. The collected gaze data were analyzed using established algorithms. Various quantitative metrics were extracted to characterize the recorded gaze patterns. The extracted metrics were correlated with the radiologists’ diagnostic decisions and perceived complexity scores. Results showed that the association between radiologists’ gaze metrics and their error making patterns varies, not only depending on the radiologists’ experience level but also among individuals. However, some gaze metrics appear to correlate with diagnostic error and perceived complexity more consistently. These results suggest that although gaze patterns are generally associated with diagnostic error and the perceived difficulty of the diagnostic task, there are substantial differences among individuals that are not explained simply by the training level of the individual performing the diagnostic task.

Paper Details

Date Published: 28 March 2013
PDF: 8 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 867302 (28 March 2013); doi: 10.1117/12.2007908
Show Author Affiliations
Sophie Voisin, Oak Ridge National Lab. (United States)
Frank Pinto, Virginia State Univ. (United States)
Songhua Xu, Oak Ridge National Lab. (United States)
Garnetta Morin-Ducote, Univ. of Tennessee Medical Ctr. (United States)
Kathy Hudson, Univ. of Tennessee Medical Ctr. (United States)
Georgia D. Tourassi, Oak Ridge National Lab. (United States)


Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)

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