Highlights
- •The CHO has been used to predict human observer performance in a detection task.
- •The correlation between human and model observer performance was assessed.
- •Aspects of the HVS were added to study the predictive value of the CHO.
- •The most useful formulation of the CHO was found to depend on the task.
- •The CHO has potential to assess image quality objectively in mammography.
Abstract
Purpose
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.
Keywords
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Article info
Publication history
Published online: December 28, 2016
Accepted:
December 21,
2016
Received in revised form:
December 12,
2016
Received:
September 29,
2016
Identification
Copyright
© 2016 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
