Abstract #3726
An Efficient MR Inhomogeneity Corrector Using Regularized Entropy Minimization
Bo Zhang 1 , Hans Peeters 2 , Ad Moerland 2 , Helene Langet 1 , and Niccolo Stefani 3
1
Philips Research, Suresnes, France,
2
Philips
Healthcare, Netherlands,
3
Philips
Healthcare, OH, United States
MR images are usually degenerated by artifact of
intensity inhomogeneity, or bias field, undesirable for
perception and diagnosis. In this work, we present an
optimized 3-dimensional retrospective nonparametric
inhomogeneity correction method by minimizing a
regularized-entropy criterion. The inhomogeneity
estimator is numerically particularly efficient,
scalable and parallelizable compared to exisiting
entropy-based approaches. Its effectiveness and
robustness have also been validated by vast clinical
evaluations on 1.5T and 3T scans of brain and breast
applications.
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