Paper
11 June 1985 Is Ideal-Observer Signal-To-Noise Ratio A Good Predictor Of Human Performance?
K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, G. W. Seeley
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Abstract
An ideal observer is a mythical detector optimized to give the best performance for a given signal detection or discrimination task. "Best" is defined here to mean that the detector is designed to yield the lowest possible Bayesian risk. The signal-to-noise ratio can be measured at the output of an ideal detector, which we will call SNRideal, and used as a figure of merit for a medical imaging system. For SNRideal to be a meaningful metric for medical images it must predict the ability of a human observer to perform the same detection or discrimination task. Images have been generated with equal ideal-observer SNR's but different autocorrelation functions to test the applicability of ideal-observer SNR for predicting human observer performance for images of different noise textures.
© (1985) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
K. J. Myers, H. H. Barrett, M. C. Borgstrom, D. D. Patton, and G. W. Seeley "Is Ideal-Observer Signal-To-Noise Ratio A Good Predictor Of Human Performance?", Proc. SPIE 0535, Application of Optical Instrumentation in Medicine XIII, (11 June 1985); https://doi.org/10.1117/12.947229
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KEYWORDS
Signal to noise ratio

Image filtering

Sensors

Imaging systems

Medical imaging

Performance modeling

Signal detection

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