SPECIAL SECTION ON MODEL-BASED MEDICAL IMAGE PROCESSING AND ANALYSIS Probabilistic Models

Bayesian model for intensity mapping in magnetic resonance image registration

[+] Author Affiliations
Alexei M. C. Machado

Pontifical Catholic University of Minas Gerais, Graduate Program in Electrical Engineering, Av. Dom Jose´ Gaspar 500, Belo Horizonte, MG, 30535-610, Brazil

Mario F. M. Campos

Federal University of Minas Gerais, Department of Computer Science, Caixa Postal 702, Belo Horizonte, MG, 30161-970, Brazil

James C. Gee

University of Pennsylvania, Department of Radiology, 3600 Market Street, Suite 370, Philadelphia, Pennsylvania?19104

J. Electron. Imaging. 12(1), 31-39 (Jan 01, 2003). doi:10.1117/1.1526845
History: Received May 1, 2001; Accepted Jun. 1, 2002; Online January 29, 2003
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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 SPIE and IS&T.

© 2003 SPIE and IS&T

Citation

Alexei M. C. Machado ; Mario F. M. Campos and James C. Gee
"Bayesian model for intensity mapping in magnetic resonance image registration", J. Electron. Imaging. 12(1), 31-39 (Jan 01, 2003). ; http://dx.doi.org/10.1117/1.1526845


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