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Proceedings Paper

Effects of grayscale window/level parameters on breast lesion detectability
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Paper Abstract

The detectability of low-contrast lesions in medical images can be affected significantly by the choice of grayscale window width and level (W/L) for electronic display. Our objective was to measure the effects of various W/L conditions on lesion detectability in simulated and real mammographic images, and then correlate observer performance with predictions of detection thresholds derived from a visual discrimination model (VDM). In the first experiment, detection thresholds were measured in 2AFC trials for five W/L conditions applied to simulated mammographic backgrounds and lesions (i.e., Gaussian "masses" and blurred-disk "microcalcification clusters") using nonmedical observers. In the second experiment, the detectability of real microcalcification clusters in digitized mammograms was evaluated for three W/L conditions in an ROC observer study with mammographers. For the simulated images, there was generally good agreement between model and experimental thresholds and their variations across W/L conditions. Both experimental and model results showed significant reductions in thresholds when W/L processing was applied locally near the lesion. ROC results with digitized mammograms read by radiologists, however, failed to show enhanced detection of microcalcifications using a localized W/L frame, probably due to the nonuniform appearance of parenchymal tissue across the image.

Paper Details

Date Published: 22 May 2003
PDF: 12 pages
Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); doi: 10.1117/12.480340
Show Author Affiliations
Jeffrey P. Johnson, Sarnoff Corp. (United States)
John S. Nafziger, Sarnoff Corp. (United States)
Elizabeth A. Krupinski, Univ. of Arizona (United States)
Jeffrey Lubin, Sarnoff Corp (United States)
Hans Roehrig, Univ. of Arizona (United States)


Published in SPIE Proceedings Vol. 5034:
Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment
Dev P. Chakraborty; Elizabeth A. Krupinski, Editor(s)

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