Mammographic Density Effect on Readers’ Performance and Visual Search Pattern

Dana S AL Mousa; Patrick C Brennan; Elaine A Ryan; Claudia Mello-Thoms

doi:10.1007/978-3-319-07887-8_25

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Mammographic Density Effect on Readers’ Performance and Visual Search Pattern

Book chapter

Peer reviewed

Mammographic Density Effect on Readers’ Performance and Visual Search Pattern

Dana S AL Mousa, Patrick C Brennan, Elaine A Ryan and Claudia Mello-Thoms

Breast Imaging, pp.174-180

Lecture Notes in Computer Science, Springer International Publishing

2014

DOI: 10.1007/978-3-319-07887-8_25

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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.

visual search pattern

readers’ performance

Mammographic breast density

digital mammography

Details

Title: Subtitle: Mammographic Density Effect on Readers’ Performance and Visual Search Pattern
Creators: Dana S AL Mousa - Department of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, Lidcombe, Australia
Patrick C Brennan - Department of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, Lidcombe, Australia
Elaine A Ryan - Department of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, Lidcombe, Australia
Claudia Mello-Thoms - Department of Medical Imaging and Radiation Sciences, Faculty of Health Sciences, University of Sydney, Lidcombe, Australia
Resource Type: Book chapter
Publication Details: Breast Imaging, pp.174-180
Publisher: Springer International Publishing; Cham
Series: Lecture Notes in Computer Science
DOI: 10.1007/978-3-319-07887-8_25
eISSN: 1611-3349
ISSN: 0302-9743
Language: English
Date published: 2014
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology
Record Identifier: 9984051501502771

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