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

Research output: Contribution to journalArticle

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)12-15
Number of pages4
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume535
DOIs
StatePublished - Jun 11 1985

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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