Document Detail


Robust tensor estimation in diffusion tensor imaging.
MedLine Citation:
PMID:  21993763     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The signal response measured in diffusion tensor imaging is subject to detrimental influences caused by noise. Noise fields arise due to various contributions such as thermal and physiological noise and sources related to the hardware imperfection. As a result, diffusion tensors estimated by different linear and non-linear least squares methods in absence of a proper noise correction tend to be substantially corrupted. In this work, we propose an advanced tensor estimation approach based on the least median squares method of the robust statistics. Both constrained and non-constrained versions of the method are considered. The performance of the developed algorithm is compared to that of the conventional least squares method and of the alternative robust methods proposed in the literature. Two examples of simulated diffusion attenuations and experimental in vivo diffusion data sets were used as a basis for comparison. The robust algorithms were shown to be advantageous compared to the least squares method in the cases where elimination of the outliers is desirable. Additionally, the constraints were applied in order to prevent generation of the non-positive definite tensors and reduce related artefacts in the maps of fractional anisotropy. The developed method can potentially be exploited also by other MR techniques where a robust regression or outlier localisation is required.
Authors:
Ivan I Maximov; Farida Grinberg; N Jon Shah
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-9-22
Journal Detail:
Title:  Journal of magnetic resonance (San Diego, Calif. : 1997)     Volume:  -     ISSN:  1096-0856     ISO Abbreviation:  -     Publication Date:  2011 Sep 
Date Detail:
Created Date:  2011-10-13     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9707935     Medline TA:  J Magn Reson     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
Copyright © 2011 Elsevier Inc. All rights reserved.
Affiliation:
Institute of Neuroscience and Medicine - 4, Forschungszentrum Juelich GmbH, 52425 Juelich, Germany.
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