Abstract
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.
Cite
CITATION STYLE
Solanas, E., & Thiran, J. P. (2001). Exploiting voxel correlation for automated MRI bias field correction by conditional entropy minimization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2208, pp. 1220–1221). Springer Verlag. https://doi.org/10.1007/3-540-45468-3_170
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