1 January 2003 Bayesian model for intensity mapping in magnetic resonance imaging image registration
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J. of Electronic Imaging, 12(1), (2003). doi:10.1117/1.1526845
We present a likelihood model for Bayesian nonrigid image registration that relates the distinct acquisition models of different MRI (magnetic resonance imaging) scanners. The model is derived from a Bayesian network that represents the imaging situation under consideration to construct the appropriate similarity measure for the given situation. The method is compared to the cross-correlation and mutual information measures in a set of registration experiments on different images and over different synthetically generated geometric and intensity distortions. The probability-based similarity measure yields, on average, more accurate and robust registrations than either the cross-correlation or mutual information measures.
Alexei Manso Correa Machado, Mario F.M. Campos, James C. Gee, "Bayesian model for intensity mapping in magnetic resonance imaging image registration," Journal of Electronic Imaging 12(1), (1 January 2003). https://doi.org/10.1117/1.1526845

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