Literature DB >> 8883705

A new decision rule for parameter delta in MAP EM (OSL) reconstruction with the Gibbs prior.

K Ogawa1, K Hiruma.   

Abstract

In MAP EM (OSL) reconstruction with the Gibbs prior, the parameter delta which appears in the prior is commonly treated as a fixed value. Because the quality of reconstructed images depends on this parameter, we have to select delta very carefully, and because the statistics of an image vary locally, we should not choose a single delta value for each image. We propose a new decision rule to select an appropriate local delta. In our proposed method, delta is determined as the median of the differences between a value of the pixel of interest and those of neighboring pixels. This selection yields an appropriate prior depending on the regional statistics. The prior therefore preserves the edge property without amplifying statistical noise and it is not necessary to know the appropriate delta value to obtain high quality images. We performed computer simulations to determine the effectiveness of the proposed method. The results showed that the quality of reconstructed images obtained with the proposed method was superior to those obtained with the prior with a fixed delta.

Mesh:

Year:  1996        PMID: 8883705     DOI: 10.1007/bf03164736

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN: 0914-7187            Impact factor:   2.668


  8 in total

1.  Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.

Authors:  S Geman; D Geman
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  1984-06       Impact factor: 6.226

2.  Simulation evaluation of Gibbs prior distributions for use in maximum a posteriori SPECT reconstructions.

Authors:  D S Lalush; B W Tsui
Journal:  IEEE Trans Med Imaging       Date:  1992       Impact factor: 10.048

3.  Convergence of EM image reconstruction algorithms with Gibbs smoothing.

Authors:  K Lange
Journal:  IEEE Trans Med Imaging       Date:  1990       Impact factor: 10.048

4.  A generalized EM algorithm for 3-D Bayesian reconstruction from Poisson data using Gibbs priors.

Authors:  T Hebert; R Leahy
Journal:  IEEE Trans Med Imaging       Date:  1989       Impact factor: 10.048

5.  A theoretical study of some maximum likelihood algorithms for emission and transmission tomography.

Authors:  K Lange; M Bahn; R Little
Journal:  IEEE Trans Med Imaging       Date:  1987       Impact factor: 10.048

6.  Maximum likelihood reconstruction for emission tomography.

Authors:  L A Shepp; Y Vardi
Journal:  IEEE Trans Med Imaging       Date:  1982       Impact factor: 10.048

7.  A generalized Gibbs prior for maximum a posteriori reconstruction in SPECT.

Authors:  D S Lalush; B M Tsui
Journal:  Phys Med Biol       Date:  1993-06       Impact factor: 3.609

8.  EM reconstruction algorithms for emission and transmission tomography.

Authors:  K Lange; R Carson
Journal:  J Comput Assist Tomogr       Date:  1984-04       Impact factor: 1.826

  8 in total

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