An ideal observer for a model of x-ray imaging in breast parenchymal tissue

Craig K. Abbey, John M Boone

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

21 Scopus citations

Abstract

We develop and evaluate an ideal observer for model of the 3D spatial distribution of x-ray attenuation coefficients in the breast. This model relies on thresholding of an underlying Gaussian random field to generate binary objects representing the distribution of adipose and glandular tissue in the breast parenchyma. Our motivation is to evaluate an emerging breast CT device for breast cancer screening. We show how the thresholded Gaussian model fits into the Markov-Chain Monte-Carlo (MCMC) approach for evaluating ideal-observer performance devised by Kupinski et al. [JOSA-A, 2003], and we show some preliminary results indicating that the procedure can be made to generate qualitatively realistic simulations. We demonstrate improved performance of the MCMC ideal observer over a Hotelling linear filter in a small-scale simulation.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages393-400
Number of pages8
Volume5116 LNCS
DOIs
StatePublished - 2008
Event9th International Workshop on Digital Mammography, IWDM 2008 - Tucson, AZ, United States
Duration: Jul 20 2008Jul 23 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5116 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other9th International Workshop on Digital Mammography, IWDM 2008
CountryUnited States
CityTucson, AZ
Period7/20/087/23/08

Keywords

  • Binary texture
  • Breast CT
  • Ideal observer
  • Screening mammography

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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