Literature DB >> 23503988

Trend of contrast detection threshold with and without localization.

David L Leong1, Louise Rainford, Tamara Miner Haygood, Gary J Whitman, William R Geiser, Beatriz E Adrada, Lumarie Santiago, Patrick C Brennan.   

Abstract

Published information on contrast detection threshold is based primarily on research using a location-known methodology. In previous work on testing the Digital Imaging and Communications in Medicine (DICOM) Grayscale Standard Display Function (GSDF) for perceptual linearity, this research group used a location-unknown methodology to more closely reflect clinical practice. A high false-positive rate resulted in a high variance leading to the conclusion that the impact on results of employing a location-known methodology needed to be explored. Fourteen readers reviewed two sets of simulated mammographic background images, one with the location-unknown and one with the location-known methodology. The results of the reader study were analyzed using Reader Operating Characteristic (ROC) methodology and a paired t test. Contrast detection threshold was analyzed using contingency tables. No statistically significant difference was found in GSDF testing, but a highly statistical significant difference (p value <0.0001) was seen in the ROC (AUC) curve between the location-unknown and the location-known methodologies. Location-known methodology not only improved the power of the GSDF test but also affected the contrast detection threshold which changed from +3 when the location was unknown to +2 gray levels for the location-known images. The selection of location known versus unknown in experimental design must be carefully considered to ensure that the conclusions of the experiment reflect the study's objectives.

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Year:  2013        PMID: 23503988      PMCID: PMC3824922          DOI: 10.1007/s10278-013-9589-4

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  16 in total

1.  Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method.

Authors:  D D Dorfman; K S Berbaum; C E Metz
Journal:  Invest Radiol       Date:  1992-09       Impact factor: 6.016

2.  Power estimation for the Dorfman-Berbaum-Metz method.

Authors:  Stephen L Hillis; Kevin S Berbaum
Journal:  Acad Radiol       Date:  2004-11       Impact factor: 3.173

3.  Assessment of display performance for medical imaging systems: executive summary of AAPM TG18 report.

Authors:  Ehsan Samei; Aldo Badano; Dev Chakraborty; Ken Compton; Craig Cornelius; Kevin Corrigan; Michael J Flynn; Bradley Hemminger; Nick Hangiandreou; Jeffrey Johnson; Donna M Moxley-Stevens; William Pavlicek; Hans Roehrig; Lois Rutz; Jeffrey Shepard; Robert A Uzenoff; Jihong Wang; Charles E Willis
Journal:  Med Phys       Date:  2005-04       Impact factor: 4.071

4.  Monte Carlo validation of the Dorfman-Berbaum-Metz method using normalized pseudovalues and less data-based model simplification.

Authors:  Stephen L Hillis; Kevin S Berbaum
Journal:  Acad Radiol       Date:  2005-12       Impact factor: 3.173

5.  A software tool for increased efficiency in observer performance studies in radiology.

Authors:  Sara Börjesson; Markus Håkansson; Magnus Båth; Susanne Kheddache; Sune Svensson; Anders Tingberg; Anna Grahn; Mark Ruschin; Bengt Hemdal; Sören Mattsson; Lars Gunnar Månsson
Journal:  Radiat Prot Dosimetry       Date:  2005       Impact factor: 0.972

6.  A comparison of denominator degrees of freedom methods for multiple observer ROC analysis.

Authors:  Stephen L Hillis
Journal:  Stat Med       Date:  2007-02-10       Impact factor: 2.373

7.  Contrast sensitivity of digital imaging display systems: contrast threshold dependency on object type and implications for monitor quality assurance and quality control in PACS.

Authors:  Jihong Wang; Jun Xu; Veera Baladandayuthapani
Journal:  Med Phys       Date:  2009-08       Impact factor: 4.071

8.  Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis.

Authors:  Stephen L Hillis; Kevin S Berbaum; Charles E Metz
Journal:  Acad Radiol       Date:  2008-05       Impact factor: 3.173

9.  Introduction to perceptual linearization of video display systems for medical image presentation.

Authors:  B M Hemminger; R E Johnston; J P Rolland; K E Muller
Journal:  J Digit Imaging       Date:  1995-02       Impact factor: 4.056

10.  Human observer detection experiments with mammograms and power-law noise.

Authors:  A E Burgess; F L Jacobson; P F Judy
Journal:  Med Phys       Date:  2001-04       Impact factor: 4.071

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