Mammographic density effect on readers' performance and visual search pattern

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Abstract

A test set of 150 digital mammograms were examined by 14 radiologists, seven of which underwent eye-position recording. Mammograms were classified into low- and high- density cases, in order to investigate the impact of density on readers' performance and visual search patterns. Lesions overlaying were compared to those outside the dense fibroglandular tissue. Our results suggest that when the lesion was overlaying the fibroglandular tissue, readers' performance significantly improved in high- compared to low- density cases. Also the dense area of breast parenchyma attracted the radiologists' visual attention, in both low- and high- mammographic density cases. When the lesions were outside the dense fibroglandular tissue, no difference was noted in radiologist' performance. In conclusion, dense areas of the breast parenchyma attracted the radiologists' visual attention, in both low- and high density cases, which might improve lesion detection when the malignancy is overlaying the dense parts of the breast tissue. © 2014 Springer International Publishing.

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APA

AL Mousa, D. S., Brennan, P. C., Ryan, E. A., & Mello-Thoms, C. (2014). Mammographic density effect on readers’ performance and visual search pattern. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8539 LNCS, pp. 174–180). Springer Verlag. https://doi.org/10.1007/978-3-319-07887-8_25

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