Radiologists' preferences for digital mammographic display

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  • Pisano, Etta D.
    • Affiliation: School of Medicine, Department of Radiology
  • Cole, Elodia B.
    • Affiliation: School of Medicine, UNC/NCSU Joint Department of Biomedical Engineering
  • Major, Stacey
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Zong, Shuquan
    • Affiliation: School of Medicine, UNC/NCSU Joint Department of Biomedical Engineering
  • Hemminger, Bradley M.
    • Affiliation: School of Medicine, Department of Radiology
  • Muller, Keith E.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Johnston, R. Eugene
    • Affiliation: School of Medicine, Department of Radiology
  • Walsh, Ruth
    • Other Affiliation: Department of Radiology, Duke University, Durham, NC
  • Conant, Emily
    • Other Affiliation: Breast Imaging Section, University of Pennsylvania Medical Center, Philadelphia
  • Fajardo, Laurie L.
    • Other Affiliation: Department of Radiology, Johns Hopkins University, Baltimore, Md
  • Feig, Stephen A.
    • Other Affiliation: Division of Breast Imaging, Mount Sinai Medical Center, New York, NY
  • Nishikawa, Robert M.
    • Other Affiliation: Department of Radiology, University of Chicago, Ill
  • Yaffe, Martin J.
    • Other Affiliation: Departments of Medical Biophysics and Medical Imaging, University of Toronto, Sunnybrook Health Sciences, Ontario, Canada
  • Williams, Mark B.
    • Other Affiliation: Department of Radiology, University of Virginia Health Sciences Center, Charlottesville
  • Aylward, Stephen
    • Affiliation: School of Medicine, Department of Radiology
Abstract
  • PURPOSE: To determine the preferences of radiologists among eight different image processing algorithms applied to digital mammograms obtained for screening and diagnostic imaging tasks. MATERIALS AND METHODS: Twenty-eight images representing histologically proved masses or calcifications were obtained by using three clinically available digital mammographic units. Images were processed and printed on film by using manual intensity windowing, histogram-based intensity windowing, mixture model intensity windowing, peripheral equalization, multiscale image contrast amplification (MUSICA), contrast-limited adaptive histogram equalization, Trex processing, and unsharp masking. Twelve radiologists compared the processed digital images with screen-film mammograms obtained in the same patient for breast cancer screening and breast lesion diagnosis. RESULTS: For the screening task, screen-film mammograms were preferred to all digital presentations, but the acceptability of images processed with Trex and MUSICA algorithms were not significantly different. All printed digital images were preferred to screen-film radiographs in the diagnosis of masses; mammograms processed with unsharp masking were significantly preferred. For the diagnosis of calcifications, no processed digital mammogram was preferred to screen-film mammograms. CONCLUSION: When digital mammograms were preferred to screen-film mammograms, radiologists selected different digital processing algorithms for each of three mammographic reading tasks and for different lesion types. Soft-copy display will eventually allow radiologists to select among these options more easily.
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  • Article
Rights statement
  • In Copyright
Journal title
  • Radiology
Journal volume
  • 216
Journal issue
  • 3
Page start
  • 820
Page end
  • 830
Language
  • English
Version
  • Postprint
ISSN
  • 0033-8419

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