1 January 2003 Bayesian model for intensity mapping in magnetic resonance imaging image registration
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Abstract
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.
© (2003) Society of Photo-Optical Instrumentation Engineers (SPIE)
Alexei Manso Correa Machado, Alexei Manso Correa Machado, Mario F.M. Campos, Mario F.M. Campos, James C. Gee, 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 . Submission:
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