title: Can the non-pre-whitening model observer, including aspects of the human visual system, predict human observer performance in mammography?
abstract: OBJECTIVE
  In mammography, images are processed prior to display. Current methodologies based on physical image quality measurements are however not designed for the evaluation of processed images. Model observers (MO) might be suitable for this evaluation. The aim of this study was to investigate whether the non-pre-whitening (NPW) MO can be used to predict human observer performance in mammography-like images by including different aspects of the human visual system (HVS).
  
  
  METHODS
  The correlation between human and NPW MO performance has been investigated for the detection of disk shaped objects in simulated white noise (WN) and clustered lumpy backgrounds (CLB), representing quantum noise limited and mammography-like images respectively. The images were scored by the MO and five human observers in a 2-alternative forced choice experiment.
  
  
  RESULTS
  For WN images it was found that the log likelihood ratio (RLR2), which expresses the goodness of fit, was highest (0.44) for the NPW MO without addition of HVS aspects. For CLB the RLR2improved from 0.46 to 0.65 with addition of HVS aspects. The correlation was affected by object size and background.
  
  
  CONCLUSIONS
  This study shows that by including aspects of the HVS, the performance of the NPW MO can be improved to better predict human observer performance. This demonstrates that the NPW MO has potential for image quality assessment. However, due to the dependencies found in the correlation, the NPW MO can only be used for image quality assessment for a limited range of object sizes and background variability.
authors.affiliation: Dutch Reference Centre for Screening (LRCB), Radboud University Medical Centre, The Netherlands. Electronic address: r.bouwman@lrcb.nl.
authors.forename: R W
authors.initials: RW
authors.lastname: Bouwman
authors.affiliation: Dutch Reference Centre for Screening (LRCB), Radboud University Medical Centre, The Netherlands.
authors.forename: R E
authors.initials: RE
authors.lastname: van Engen
authors.affiliation: Dutch Reference Centre for Screening (LRCB), Radboud University Medical Centre, The Netherlands; Radboud Institute for Health Sciences (RIHS), Radboud University Medical Centre, The Netherlands.
authors.forename: M J M
authors.initials: MJ
authors.lastname: Broeders
authors.affiliation: Dutch Reference Centre for Screening (LRCB), Radboud University Medical Centre, The Netherlands; Department of Radiology, Academic Medical Centre (AMC), The Netherlands.
authors.forename: G J
authors.initials: GJ
authors.lastname: den Heeten
authors.affiliation: National Co-ordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey County Hospital, United Kingdom; Department of Physics, University of Surrey, United Kingdom.
authors.forename: D R
authors.initials: DR
authors.lastname: Dance
authors.affiliation: National Co-ordinating Centre for the Physics of Mammography (NCCPM), Royal Surrey County Hospital, United Kingdom; Department of Physics, University of Surrey, United Kingdom.
authors.forename: K C
authors.initials: KC
authors.lastname: Young
authors.affiliation: Dutch Reference Centre for Screening (LRCB), Radboud University Medical Centre, The Netherlands; Department of Radiology, Leiden University Medical Centre (LUMC), The Netherlands.
authors.forename: W J H
authors.initials: WJ
authors.lastname: Veldkamp
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008327:Mammography; D008954:Models, Biological; D015588:Observer Variation; D059629:Signal-To-Noise Ratio; D014796:Visual Perception
keywords: Clinical image quality; Contrast sensitivity function; Mammography; Model observer