Model selection in ultrasonic measurements on trabecular bone

Christian C. Anderson, Karen R. Marutyan, Keith A. Wear, Mark R. Holland, James G. Miller, G. Larry Bretthorst

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Previous work from our laboratory showed that the widely reported decrease in phase velocity with frequency (negative dispersion) for ultrasonic waves propagating through trabecular bone can arise from the interference of two compressional waves, each of which exhibits a positive dispersion. Previous simulations suggest that Bayesian probability theory can be employed to recover the material properties linked to these two interfering waves, even when the waves overlap sufficiently that visual inspection cannot distinguish two modes. In the present study, Bayesian probability theory is applied first to simulated data and then to representative experimental bone data to determine whether one or two compressional wave modes are present. Model selection is implemented by evaluating the posterior probability for each model. The calculation is implemented by defining a model indicator and then using Markov chain Monte Carlo with simulated annealing to draw samples from the joint posterior probability for the ultrasonic parameters and the model indicator. Monte Carlo integration is used to evaluate the marginal posterior probability for each parameter given the model indicator.

Original languageEnglish
Title of host publicationBayesian Inference and Maximum Entropy Methods in Science and Engineering - 27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007
Pages337-345
Number of pages9
DOIs
StatePublished - 2007
Event27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007 - Saratoga Springs, NY, United States
Duration: Jul 8 2007Jul 13 2007

Publication series

NameAIP Conference Proceedings
Volume954
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference27th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2007
Country/TerritoryUnited States
CitySaratoga Springs, NY
Period07/8/0707/13/07

Keywords

  • Bayesian probability theory
  • Bone
  • Model selection
  • Osteoporosis
  • Tissue characterization
  • Ultrasound

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