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Proceedings Paper

Effect of selective suppression of spatial frequency domain noise on visual detection of a sample object in an inhomogeneous background
Author(s): Mariusz W. Pietrzyk; J. Scott McDonald; Patrick C. Brennan; Roger M. Bourne
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Paper Abstract

This study aims to investigate the effect of selective suppression of spatial frequency (SF) domain Gaussian white noise on visibility of a sample object in inhomogeneous backgrounds. SF-specific variation in signal-to-noise ratio due to selective signal averaging in the SF domain is a consequence of some of MRI acquisition methods. This study models the potential effect on visibility of an object in a complex image. A single disc was randomly positioned in 25 of 50 synthetic clustered lumpy background images. Neutral, low mid and high frequency suppressed Gaussian white noise was added in the frequency domain to simulate SF-weighted MRI signal averaging. Twelve readers performed visual searching and localization tasks on ordered sets. Subjects were asked to detect and locate discs and to rank confidence level. Sensitivity, specificity and ROC analyses were performed. Readers achieved significantly higher ROC AUC - Azscores - (p<0.001) and case-based sensitivity (p<0.001) and target-based sensitivity (p<0.001) with images in which low SF noise was suppressed. Also, significant higher cased-based sensitivity (p=0.005), target-based sensitivity (p=0.022) and Az-values (p=0.01) were scored under mid SF noise filtration. No significant differences were observed when images with SF-neutral noise suppression were compared with high SF noise suppression. In conclusion, increase of low and also mid SF signal signal-to-noise ratio significantly improves human performance in visual detection of simple targets in inhomogeneous backgrounds and suggests that a low SF bias in MRI signal averaging may enhance diagnostic quality.

Paper Details

Date Published: 22 February 2012
PDF: 10 pages
Proc. SPIE 8318, Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment, 831817 (22 February 2012); doi: 10.1117/12.911638
Show Author Affiliations
Mariusz W. Pietrzyk, The Univ. of Sydney (Australia)
J. Scott McDonald, The Univ. of New South Wales (Australia)
Patrick C. Brennan, The Univ. of Sydney (Australia)
Roger M. Bourne, The Univ. of Sydney (Australia)


Published in SPIE Proceedings Vol. 8318:
Medical Imaging 2012: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)

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