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Proceedings Paper

Effect of image processing version on detection of non-calcification cancers in 2D digital mammography imaging
Author(s): L. M. Warren; J. Cooke; R. M. Given-Wilson; M. G. Wallis; M. Halling-Brown; A. Mackenzie; D. P. Chakraborty; H. Bosmans; D. R. Dance; K. C. Young
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Paper Abstract

Image processing (IP) is the last step in the digital mammography imaging chain before interpretation by a radiologist. Each manufacturer has their own IP algorithm(s) and the appearance of an image after IP can vary greatly depending upon the algorithm and version used. It is unclear whether these differences can affect cancer detection. This work investigates the effect of IP on the detection of non-calcification cancers by expert observers. Digital mammography images for 190 patients were collected from two screening sites using Hologic amorphous selenium detectors. Eighty of these cases contained non-calcification cancers. The images were processed using three versions of IP from Hologic – default (full enhancement), low contrast (intermediate enhancement) and pseudo screen-film (no enhancement). Seven experienced observers inspected the images and marked the location of regions suspected to be non-calcification cancers assigning a score for likelihood of malignancy. This data was analysed using JAFROC analysis. The observers also scored the clinical interpretation of the entire case using the BSBR classification scale. This was analysed using ROC analysis. The breast density in the region surrounding each cancer and the number of times each cancer was detected were calculated. IP did not have a significant effect on the radiologists’ judgment of the likelihood of malignancy of individual lesions or their clinical interpretation of the entire case. No correlation was found between number of times each cancer was detected and the density of breast tissue surrounding that cancer.

Paper Details

Date Published: 28 March 2013
PDF: 10 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 86730O (28 March 2013); doi: 10.1117/12.2008494
Show Author Affiliations
L. M. Warren, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
J. Cooke, Jarvis Breast Screening and Diagnostic Ctr. (United Kingdom)
R. M. Given-Wilson, St George’s Healthcare NHS Trust (United Kingdom)
M. G. Wallis, Cambridge Univ. Hospitals NHS Foundation Trust (United Kingdom)
NIHR Cambridge Biomedical Research Ctr. (United Kingdom)
M. Halling-Brown, The Royal Surrey County Hospital NHS Trust (United Kingdom)
A. Mackenzie, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
D. P. Chakraborty, Univ. of Pittsburgh (United States)
H. Bosmans, Univ. Hospitals Leuven (Belgium)
D. R. Dance, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)
K. C. Young, The Royal Surrey County Hospital NHS Trust (United Kingdom)
Univ. of Surrey (United Kingdom)


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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