Approximate maximum likelihood estimation of scanning observer templates

Craig K. Abbey, Frank W. Samuelson, Adam Wunderlich, Lucretiu M. Popescu, Miguel P. Eckstein, John M Boone

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

2 Scopus citations


In localization tasks, an observer is asked to give the location of some target or feature of interest in an image. Scanning linear observer models incorporate the search implicit in this task through convolution of an observer template with the image being evaluated. Such models are becoming increasingly popular as predictors of human performance for validating medical imaging methodology. In addition to convolution, scanning models may utilize internal noise components to model inconsistencies in human observer responses. In this work, we build a probabilistic mathematical model of this process and show how it can, in principle, be used to obtain estimates of the observer template using maximum likelihood methods. The main difficulty of this approach is that a closed form probability distribution for a maximal location response is not generally available in the presence of internal noise. However, for a given image we can generate an empirical distribution of maximal locations using Monte-Carlo sampling. We show that this probability is well approximated by applying an exponential function to the scanning template output. We also evaluate log-likelihood functions on the basis of this approximate distribution. Using 1,000 trials of simulated data as a validation test set, we find that a plot of the approximate log-likelihood function along a single parameter related to the template profile achieves its maximum value near the true value used in the simulation. This finding holds regardless of whether the trials are correctly localized or not. In a second validation study evaluating a parameter related to the relative magnitude of internal noise, only the incorrect localization images produces a maximum in the approximate log-likelihood function that is near the true value of the parameter.

Original languageEnglish (US)
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
ISBN (Print)9781628415063
StatePublished - 2015
EventMedical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment - Orlando, United States
Duration: Feb 25 2015Feb 26 2015


OtherMedical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment
Country/TerritoryUnited States


  • and observer modeling
  • localization task
  • ramp-spectrum noise
  • Scanning linear template
  • search models

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


Dive into the research topics of 'Approximate maximum likelihood estimation of scanning observer templates'. Together they form a unique fingerprint.

Cite this