Bayesian Transmission Image Reconstruction Using Compound Gauss-Markov Prior Models. López, A, Garrido, J, Molina, R, & Katsaggelos, A K ICIP, 2005.
Bayesian Transmission Image Reconstruction Using Compound Gauss-Markov Prior Models [link]Paper  abstract   bibtex   
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.
@article{lopezbayesian,
abstract = {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.},
author = {L{\'{o}}pez, A and Garrido, J and Molina, R and Katsaggelos, A K},
journal = {ICIP},
title = {{Bayesian Transmission Image Reconstruction Using Compound Gauss-Markov Prior Models}},
url = {https://www.academia.edu/2704617/BAYESIAN_TRANSMISSION_IMAGE_RECONSTRUCTION_USING_COMPOUND_GAUSS_MARKOV_PRIOR_MODELS},
year = {2005}
}

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