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Journal of Digital Imaging

, Volume 25, Issue 5, pp 662–669 | Cite as

Verification of DICOM GSDF in Complex Backgrounds

  • David L. Leong
  • Louise Rainford
  • Tamara Miner Haygood
  • Gary J. Whitman
  • Philip M. Tchou
  • William R. Geiser
  • Selin Carkaci
  • Patrick C. Brennan
Article

Abstract

While previous research has determined the contrast detection threshold in medical images, it has focused on uniform backgrounds, has not used calibrated monitors, or has involved a low number of readers. With complex clinical images, how the Grayscale Standard Display Function (GSDF) affects the detection threshold and whether the median background intensity shift has been minimized by GSDF remains unknown. We set out to determine if the median background affected the detection of a low-contrast object in a clustered lumpy background, which simulated a mammography image, and to define the contrast detection threshold for these complex images. Clustered lumpy background images were created of different median intensities and disks of varying contrasts were inserted. A reader study was performed with 17 readers of varying skill level who scored with a five-point confidence scale whether a disk was present. The results were analyzed using reader operating characteristic (ROC) methodology. Contingency tables were used to determine the contrast detection threshold. No statistically significant difference was seen in the area under the ROC curve across all of the backgrounds. Contrast detection fell below 50 % between +3 and +2 gray levels. Our work supports the conclusion that Digital Imaging and Communications in Medicine GSDF calibrated monitors do perceptually linearize detection performance across shifts in median background intensity. The contrast detection threshold was determined to be +3 gray levels above the background for an object of 1° visual angle.

Keywords

Image perception ROC-based analysis Digital display Contrast threshold GSDF 

Notes

Acknowledgments

The authors would like to acknowledge all of the readers who participated in this study for their support of this research.

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Copyright information

© Society for Imaging Informatics in Medicine 2012

Authors and Affiliations

  • David L. Leong
    • 1
    • 2
  • Louise Rainford
    • 2
  • Tamara Miner Haygood
    • 3
  • Gary J. Whitman
    • 3
  • Philip M. Tchou
    • 5
  • William R. Geiser
    • 5
  • Selin Carkaci
    • 3
  • Patrick C. Brennan
    • 4
  1. 1.Analogic CorporationPeabodyUSA
  2. 2.Diagnostic Imaging, UCD School of Medicine and Medical SciencesUniversity College DublinDublin 4Ireland
  3. 3.Department of Diagnostic RadiologyThe University of Texas MD Anderson Cancer CenterHoustonUSA
  4. 4.Brain and Mind Research Institute, Faculty of Health ScienceUniversity of SydneySydneyAustralia
  5. 5.Department of Imaging PhysicsThe University of Texas MD Anderson Cancer CenterHoustonUSA

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