Document Detail


Improved diffusion imaging through SNR-enhancing joint reconstruction.
MedLine Citation:
PMID:  22392528     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Quantitative diffusion imaging is a powerful technique for the characterization of complex tissue microarchitecture. However, long acquisition times and limited signal-to-noise ratio represent significant hurdles for many in vivo applications. This article presents a new approach to reduce noise while largely maintaining resolution in diffusion weighted images, using a statistical reconstruction method that takes advantage of the high level of structural correlation observed in typical datasets. Compared to existing denoising methods, the proposed method performs reconstruction directly from the measured complex k-space data, allowing for gaussian noise modeling and theoretical characterizations of the resolution and signal-to-noise ratio of the reconstructed images. In addition, the proposed method is compatible with many different models of the diffusion signal (e.g., diffusion tensor modeling and q-space modeling). The joint reconstruction method can provide significant improvements in signal-to-noise ratio relative to conventional reconstruction techniques, with a relatively minor corresponding loss in image resolution. Results are shown in the context of diffusion spectrum imaging tractography and diffusion tensor imaging, illustrating the potential of this signal-to-noise ratio-enhancing joint reconstruction approach for a range of different diffusion imaging experiments.
Authors:
Justin P Haldar; Van J Wedeen; Marzieh Nezamzadeh; Guangping Dai; Michael W Weiner; Norbert Schuff; Zhi-Pei Liang
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2012-03-05
Journal Detail:
Title:  Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine     Volume:  69     ISSN:  1522-2594     ISO Abbreviation:  Magn Reson Med     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2012-12-20     Completed Date:  2013-06-07     Revised Date:  2014-09-21    
Medline Journal Info:
Nlm Unique ID:  8505245     Medline TA:  Magn Reson Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  277-89     Citation Subset:  IM    
Copyright Information:
Copyright © 2011 Wiley Periodicals, Inc.
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MeSH Terms
Descriptor/Qualifier:
Animals
Brain
Computer Simulation
Diffusion Magnetic Resonance Imaging / methods*
Humans
Image Processing, Computer-Assisted*
Mice
Grant Support
ID/Acronym/Agency:
P41 RR013642/RR/NCRR NIH HHS; P41 RR013642-02/RR/NCRR NIH HHS; P41 RR023953/RR/NCRR NIH HHS; P41 RR023953-01A1/RR/NCRR NIH HHS; P41-RR013642/RR/NCRR NIH HHS; P41-RR023953/RR/NCRR NIH HHS; P50 NS019632-25/NS/NINDS NIH HHS; P50-NS019632/NS/NINDS NIH HHS; R01 EB000473/EB/NIBIB NIH HHS; R01 EB000473-01A1/EB/NIBIB NIH HHS; R01 EB013695/EB/NIBIB NIH HHS; R01 NS074980/NS/NINDS NIH HHS; R01 NS074980-01/NS/NINDS NIH HHS; R01-EB000473/EB/NIBIB NIH HHS; R01-NS074980/NS/NINDS NIH HHS; U24-RR021760/RR/NCRR NIH HHS
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