Retrospective Correction of MR Intensity Inhomogeneity by Information Minimization
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
From error probability to information theoretic (multi-modal) signal processing
Signal Processing - Special issue: Information theoretic signal processing
A new method for MR grayscale inhomogeneity correction
Artificial Intelligence Review
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An unsupervised model-based strategy for bias field correction is proposed. We assume that information (in the sense of the information theory) in the corrupted image is greater than that in the uncorrupted one. The method exploits the fact that neighboring voxels are highly correlated to correct the bias field using a linear model.