title: Can the channelized Hotelling observer including aspects of the human visual system predict human observer performance in mammography?
abstract: OBJECTIVE
  In mammography, images are processed prior to display. Model observers (MO) are candidates to objectively evaluate processed images if they can predict human observer performance for detail detection. The aim of this study was to investigate if the channelized Hotelling observer (CHO) can be configured to predict human observer performance in mammography like images.
  
  
  METHODS
  The performance correlation between human observers and CHO has been evaluated using different channel-sets and by including aspects of the human visual system (HVS). The correlation was investigated for the detection of disk-shaped details in simulated white noise (WN) and clustered lumpy backgrounds (CLB) images, representing respectively quantum noise limited and mammography like images. The images were scored by the MO and five human observers in 2-alternative forced choice experiments.
  
  
  RESULTS
  For WN images the most useful formulation of the CHO to predict human observer performance was obtained using three difference of Gaussian channels without adding HVS aspects (RLR2=0.62). For CLB images the most useful formulation was the partial least square channel-set without adding HVS aspects (RLR2=0.71). The correlation was affected by detail size and background.
  
  
  CONCLUSIONS
  This study has shown that the CHO can predict human observer performance. Due to object size and background dependency it is important that the range of object sizes and allowed variability in background are specified and validated carefully before the CHO can be implemented for objective image quality assessment.
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: Department of Medical Physics, Elisabeth TweeSteden ziekenhuis, The Netherlands.
authors.forename: M
authors.initials: M
authors.lastname: Goffi
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: 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: D000465:Algorithms; D003657:Decision Making; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008327:Mammography; D016011:Normal Distribution; D011829:Radiation Dosage; D059629:Signal-To-Noise Ratio; D014796:Visual Perception
keywords: Clinical image quality; Human visual system; Mammography; Model observer