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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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