@incollection{Antonio2005,
abstract = {In this work we propose a new method to estimate the scale hyperparameter for transmission tomography in Nuclear Medicine image reconstruction problems. Within the Bayesian paradigm, Evidence Analysis and circulant preconditioners are used to obtain the scale hyperparameter. For the prior distribution, we use Generalized Gaussian Markov Random Fields (GGMRF), a nonquadratic function that preserves the edges in the reconstructed image. The experimental results indicate that the proposed method produces satisfactory reconstructions. {\textcopyright} Springer-Verlag Berlin Heidelberg 2005.},
author = {L{\'{o}}pez, Antonio and Molina, Rafael and Katsaggelos, Aggelos K.},
booktitle = {Lecture Notes in Computer Science},
doi = {10.1007/11492542_56},
issn = {03029743},
number = {II},
pages = {455--462},
title = {{Bayesian Reconstruction for Transmission Tomography with Scale Hyperparameter Estimation}},
url = {http://link.springer.com/10.1007/11492542_56},
volume = {3523},
year = {2005}
}

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