Transmission tomography reconstruction using compound Gauss-Markov random fields and ordered subsets

A. López*, J. M. Martín, R. Molina, A. K. Katsaggelos

*Corresponding author for this work

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

1 Scopus citations

Abstract

Emission tomography images are degraded due to the presence of noise and several physical factors, like attenuation and scattering. To remove the attenuation effect from the emission tomography reconstruction, attenuation correction factors (ACFs) are used. These ACFs are obtained from a transmission scan and it is well known that they are homogeneous within each tissue and present abrupt variations in the transition between tissues. In this paper we propose the use of compound Gauss Markov random fields (CGMRF) as prior distributions to model homogeneity within tissues and high variations between regions. In order to find the maximum a posteriori (MAP) estimate of the reconstructed image we propose a new iterative method, which is stochastic for the line process and deterministic for the reconstruction. We apply the ordered subsets (OS) principle to accelerate the image reconstruction. The proposed method is tested and compared with other reconstruction methods.

Original languageEnglish (US)
Title of host publicationImage Analysis and Recognition - Third International Conference, ICIAR 2006, Proceedings
PublisherSpringer Verlag
Pages559-569
Number of pages11
ISBN (Print)3540448942, 9783540448945
DOIs
StatePublished - Jan 1 2006
Event3rd International Conference on Image Analysis and Recognition, ICIAR 2006 - Povoa de Varzim, Portugal
Duration: Sep 18 2006Sep 20 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4142 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd International Conference on Image Analysis and Recognition, ICIAR 2006
CountryPortugal
CityPovoa de Varzim
Period9/18/069/20/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    López, A., Martín, J. M., Molina, R., & Katsaggelos, A. K. (2006). Transmission tomography reconstruction using compound Gauss-Markov random fields and ordered subsets. In Image Analysis and Recognition - Third International Conference, ICIAR 2006, Proceedings (pp. 559-569). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4142 LNCS). Springer Verlag. https://doi.org/10.1007/11867661_50