1 January 2003 Bayesian model for intensity mapping in magnetic resonance imaging image registration
Author Affiliations +
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, Mario F.M. Campos, and 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
Published: 1 January 2003
Lens.org Logo
CITATIONS
Cited by 3 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image registration

Tissues

Scanners

Magnetic resonance imaging

Image segmentation

Image processing

Instrument modeling

Back to Top