Document Detail


Susceptibility mapping in the human brain using threshold-based k-space division.
MedLine Citation:
PMID:  20432300     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
A method for calculating quantitative three-dimensional susceptibility maps from field measurements acquired using gradient echo imaging at high field is presented. This method is based on division of the three-dimensional Fourier transforms of high-pass-filtered field maps by a simple function that is the Fourier transform of the convolution kernel linking field and susceptibility, and uses k-space masking to avoid noise enhancement in regions where this function is small. Simulations were used to show that the method can be applied to data acquired from objects that are oriented at one angle or multiple angles with respect to the applied field and that the use of multiple orientations improves the quality of the calculated susceptibility maps. As part of this work, we developed an improved approach for high-pass filtering of field maps, based on using an arrangement of dipoles to model the fields generated by external structures. This approach was tested on simulated field maps from the substantia nigra and red nuclei. Susceptibility mapping was successfully applied to experimental measurements on a structured phantom and then used to make measurements of the susceptibility of the red nuclei and substantia nigra in healthy subjects at 3 and 7 T.
Authors:
Sam Wharton; Andreas Schäfer; Richard Bowtell
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine     Volume:  63     ISSN:  1522-2594     ISO Abbreviation:  Magn Reson Med     Publication Date:  2010 May 
Date Detail:
Created Date:  2010-04-30     Completed Date:  2010-08-05     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8505245     Medline TA:  Magn Reson Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1292-304     Citation Subset:  IM    
Copyright Information:
(c) 2010 Wiley-Liss, Inc.
Affiliation:
Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Brain / anatomy & histology*
Humans
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging / instrumentation,  methods*
Phantoms, Imaging
Reproducibility of Results
Sensitivity and Specificity

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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