Abstract
A method to estimate the magnitude MR data from several noisy samples is presented. It is based on the Linear Minimum Mean Squared Error (LMMSE) estimator for the Rician noise model when several scanning repetitions are available. This method gives a closed-form analytical solution that takes into account the probability distribution of the data as well as the existing level of noise, showing a better performance than methods such as the average or the median.
Publication types
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Research Support, N.I.H., Extramural
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms*
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Artifacts*
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Brain / anatomy & histology*
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Computer Simulation
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Diffusion Magnetic Resonance Imaging / methods
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Humans
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Image Enhancement / methods*
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Image Interpretation, Computer-Assisted / methods*
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Least-Squares Analysis
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Linear Models
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Magnetic Resonance Imaging / methods*
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Models, Biological
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Models, Statistical
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Reproducibility of Results
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Sensitivity and Specificity