Observer signal-to-noise ratios for the ML-EM algorithm

Craig K. Abbey, Harrison H. Barrett, Donald W. Wilson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

47 Scopus citations


We have used an approximate method developed by Barrett, Wilson, and Tsui for finding the ensemble statistics of the maximum likelihood-expectation maximization algorithm to compute task-dependent figures of merit as a function of stopping point. For comparison, human- observer performance was assessed through conventional psychophysics. The results of our studies show the dependence of the optimal stopping point of the algorithm on the detection task. Comparisons of human and various model observers show that a channelized Hotelling observer with overlapping channels is the best predictor of human performance.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsHarold L. Kundel
Number of pages12
StatePublished - 1996
EventMedical Imaging 1996: Image Perception - Newport Beach, CA, USA
Duration: Feb 14 1996Feb 14 1996

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherMedical Imaging 1996: Image Perception
CityNewport Beach, CA, USA

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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