Title
Nonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance imagesNonlocal maximum likelihood estimation method for denoising multiple-coil magnetic resonance images
Author
Faculty/Department
Faculty of Sciences. Physics
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences . Biomedical Sciences
Research group
Vision lab
Bio-Imaging lab
Department of Biomedical Sciences
Publication type
article
Publication
New York,
Subject
Physics
Biology
Human medicine
Computer. Automation
Source (journal)
Magnetic resonance imaging. - New York
Volume/pages
30(2012):10, p. 1512-1518
ISSN
0730-725X
ISI
000311261000019
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Effective denoising is vital for proper analysis and accurate quantitative measurements from magnetic resonance (MR) images. Even though many methods were proposed to denoise MR images, only few deal with the estimation of true signal from MR images acquired with phased-array coils. If the magnitude data from phased array coils are reconstructed as the root sum of squares, in the absence of noise correlations and subsampling, the data is assumed to follow a non central-χ distribution. However, when the k-space is subsampled to increase the acquisition speed (as in GRAPPA like methods), noise becomes spatially varying. In this note, we propose a method to denoise multiple-coil acquired MR images. Both the non central-χ distribution and the spatially varying nature of the noise is taken into account in the proposed method. Experiments were conducted on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method.
E-info
https://repository.uantwerpen.be/docman/iruaauth/1c2ec0/a88b3e38c5d.pdf
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