Uncertainty estimation in reconstructed deformable models

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One of the hallmarks of the Bayesian approach to modeling is the posterior probability, which summarizes all uncertainties regarding the analysis. Using a Markov Chain Monte Carlo (MCMC) technique, it is possible to generate a sequence of objects that represent random samples drawn from the posterior distribution. We demonstrate this technique for reconstructions of two-dimensional objects from noisy projections taken from two directions. The reconstructed object is modeled in terms of a deformable geometrically-defined boundary with a constant interior density yielding a nonlinear reconstruction problem. We show how an MCMC sequence can be used to estimate uncertainties in the location ... continued below

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11 p.

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Hanson, K.M.; Cunningham, G.S. & McKee, R. December 31, 1996.

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Description

One of the hallmarks of the Bayesian approach to modeling is the posterior probability, which summarizes all uncertainties regarding the analysis. Using a Markov Chain Monte Carlo (MCMC) technique, it is possible to generate a sequence of objects that represent random samples drawn from the posterior distribution. We demonstrate this technique for reconstructions of two-dimensional objects from noisy projections taken from two directions. The reconstructed object is modeled in terms of a deformable geometrically-defined boundary with a constant interior density yielding a nonlinear reconstruction problem. We show how an MCMC sequence can be used to estimate uncertainties in the location of the edge of the reconstructed object.

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11 p.

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OSTI as DE97003134

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  • Workshop on maximum entropy and bayesian methods, Kruger National Park (South Africa), 13-16 Aug 1996

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  • Other: DE97003134
  • Report No.: LA-UR--96-4437
  • Report No.: CONF-9608189--1
  • Grant Number: W-7405-ENG-36
  • Office of Scientific & Technical Information Report Number: 459819
  • Archival Resource Key: ark:/67531/metadc678122

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  • December 31, 1996

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  • July 25, 2015, 2:21 a.m.

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  • March 10, 2016, 1:19 p.m.

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Hanson, K.M.; Cunningham, G.S. & McKee, R. Uncertainty estimation in reconstructed deformable models, article, December 31, 1996; New Mexico. (digital.library.unt.edu/ark:/67531/metadc678122/: accessed January 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.