Is ideal-observer signal-to-noise ratio a good predictor of human performance?

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.