Literature DB >> 18044590

Signal LMMSE estimation from multiple samples in MRI and DT-MRI.

S Aja-Fernández1, C Alberola-López, C F Westin.   

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.

Mesh:

Year:  2007        PMID: 18044590     DOI: 10.1007/978-3-540-75759-7_45

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  4 in total

1.  Restoration of DWI data using a Rician LMMSE estimator.

Authors:  Santiago Aja-Fernandez; Marc Niethammer; Marek Kubicki; Martha E Shenton; Carl-Fredrik Westin
Journal:  IEEE Trans Med Imaging       Date:  2008-10       Impact factor: 10.048

2.  Fast approximate stochastic tractography.

Authors:  Juan Eugenio Iglesias; Paul M Thompson; Cheng-Yi Liu; Zhuowen Tu
Journal:  Neuroinformatics       Date:  2012-01

3.  Modeling diffusion-weighted MRI as a spatially variant gaussian mixture: application to image denoising.

Authors:  Juan Eugenio Iglesias Gonzalez; Paul M Thompson; Aishan Zhao; Zhuowen Tu
Journal:  Med Phys       Date:  2011-07       Impact factor: 4.071

4.  Bias of least squares approaches for diffusion tensor estimation from array coils in DT-MRI.

Authors:  Antonio Tristán-Vega; Carl-Fredrik Westin; Santiago Aja-Fernández
Journal:  Med Image Comput Comput Assist Interv       Date:  2009
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.