Fundamentals of statistical signal processing: estimation theory
Fundamentals of statistical signal processing: estimation theory
Probability Distributions Involving Gaussian Random Variables: A Handbook for Engineers, Scientists and Mathematicians
Rician noise removal in diffusion tensor MRI
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Joint LMMSE Estimation of DWI Data for DTI Processing
MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
Bias of Least Squares Approaches for Diffusion Tensor Estimation from Array Coils in DT---MRI
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part I
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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.