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Analysis of visual search behaviour from experienced radiologists interpreting digital breast tomosynthesis (DBT) images: a pilot study
Author(s): Leng Dong; Qiang Tang; Alastair Gale; Daniella Bernardi; Yan Chen
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Paper Abstract

Digital Breast Tomosynthesis has several advantages over traditional 2D mammography. However, the cost-effectiveness to implement DBT modality into breast screening programmes is still under investigation. The DBT modality has been integrated into a regional breast screening program in Italy for several years. The purpose of this study is to examine the experienced Italian DBT readers’ visual search behaviour and summarise their visual inspection patterns. Seven experienced radiologists took part in the study, reading a set of DBT cases with a mixture of both normal and abnormal cases whilst their eye movements data were recorded. They read the cases through a fixed procedure starting with a 2D overview and then went through the DBT view of each side of the breasts. It was found that the experienced readers tended to perform a global-focal scan over the 2D view to detect the abnormality and then ‘drilled’ through the DBT slices, interpreting the details of the feature. The reading speed was also investigated to see if there was any difference in length of time when expert radiologists examine both normal and abnormal cases. The results showed that there was no significant difference in time between normal and abnormal cases. The eye movement patterns revealed that experienced DBT readers covered more areas on the 2D view and fixated longer and with more dwells inside the AOI in the 3D view. Based on these findings it is hoped that by understanding the visual search patterns of the experienced DBT radiologists, it could potentially help DBT trainees to develop more efficient interpretation approaches.

Paper Details

Date Published: 19 March 2018
PDF: 6 pages
Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 1057707 (19 March 2018); doi: 10.1117/12.2293615
Show Author Affiliations
Leng Dong, Loughborough Univ. (United Kingdom)
Qiang Tang, Loughborough Univ. (United Kingdom)
Alastair Gale, Loughborough Univ. (United Kingdom)
Daniella Bernardi, Trento Hospital (Italy)
Yan Chen, Loughborough Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 10577:
Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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