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|Title: ||Breast screening: visual search as an aid for digital mammographic interpretation training|
|Authors: ||Chen, Yan|
Gale, Alastair G.
Scott, Hazel J.
|Keywords: ||Mammographic interpretation training|
Low resolution devices
|Issue Date: ||2010|
|Publisher: ||© 2010 Society of Photo-Optical Instrumentation Engineers|
|Citation: ||CHEN, Y. ... et al., 2010. Breast screening: visual search as an aid for digital mammographic interpretation training. IN: Medical Imaging 2010: Image Perception, Observer Performance, and Technology Assessment, edited by David J. Manning, Craig K. Abbey, Proc. SPIE 7627,76270C (2010).|
|Abstract: ||Digital mammography is gradually being introduced across all breast screening centres in the UK during 2010. This
provides increased training opportunities using lower resolution, lower cost and more widely available devices, in
addition to the clinical digital mammography workstations. This study examined how experienced breast screening
personnel performed when they examined sets of difficult DICOM two-view screening cases in three conditions: on GE
digital mammography workstations, on a standard LCD monitor (using a DICOM viewer) and an iPhone (running Osirix
software). In each condition they either viewed the full images unaided or were permitted to use the post-processing
manipulations of pan, zoom and window level/width adjustments. For each case they had to report the feature type, rate
their confidence on the presence of abnormality, classify the case and specify case density. Their visual search behaviour
was recorded throughout using a head mounted eye tracker. Additionally aspects of their real life screening performance
and performance on a national self assessment scheme were examined. Data indicate that screening experience plays a
major role in doing well on the self assessment scheme. Task performance was best on the clinical workstation.
However, the data also suggest that a DICOM viewer that runs on a PC or laptop with a standard LCD display allows
viewing digital images in full resolution support impressive cancer detection performance. The iPhone is not ideal for
examining full images due to the amount of scrolling and zooming required. Overall, the results indicate that low cost
devices could be used to provide additional tailored training as long as device resolution and HCI aspects are carefully
|Description: ||Copyright 2010 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. This paper can also be found at: http://dx.doi.org/10.1117/12.843820|
|Appears in Collections:||Conference Papers and Presentations (Computer Science)|
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