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Characterization of anomalous relaxation using the time‐fractional Bloch equation and multiple echo T2*‐weighted magnetic resonance imaging at 7 T

Overview of attention for article published in Magnetic Resonance in Medicine, March 2016
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Title
Characterization of anomalous relaxation using the time‐fractional Bloch equation and multiple echo T2*‐weighted magnetic resonance imaging at 7 T
Published in
Magnetic Resonance in Medicine, March 2016
DOI 10.1002/mrm.26222
Pubmed ID
Authors

Shanlin Qin, Fawang Liu, Ian W. Turner, Qiang Yu, Qianqian Yang, Viktor Vegh

Abstract

To study the utility of fractional calculus in modeling gradient-recalled echo MRI signal decay in the normal human brain. We solved analytically the extended time-fractional Bloch equations resulting in five model parameters, namely, the amplitude, relaxation rate, order of the time-fractional derivative, frequency shift, and constant offset. Voxel-level temporal fitting of the MRI signal was performed using the classical monoexponential model, a previously developed anomalous relaxation model, and using our extended time-fractional relaxation model. Nine brain regions segmented from multiple echo gradient-recalled echo 7 Tesla MRI data acquired from five participants were then used to investigate the characteristics of the extended time-fractional model parameters. We found that the extended time-fractional model is able to fit the experimental data with smaller mean squared error than the classical monoexponential relaxation model and the anomalous relaxation model, which do not account for frequency shift. We were able to fit multiple echo time MRI data with high accuracy using the developed model. Parameters of the model likely capture information on microstructural and susceptibility-induced changes in the human brain. Magn Reson Med, 2016. © 2016 Wiley Periodicals, Inc.

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The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Germany 1 5%
Unknown 19 90%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 38%
Student > Ph. D. Student 3 14%
Student > Bachelor 2 10%
Professor 2 10%
Student > Master 1 5%
Other 2 10%
Unknown 3 14%
Readers by discipline Count As %
Medicine and Dentistry 5 24%
Neuroscience 3 14%
Engineering 2 10%
Physics and Astronomy 2 10%
Biochemistry, Genetics and Molecular Biology 1 5%
Other 2 10%
Unknown 6 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 March 2016.
All research outputs
#22,756,649
of 25,371,288 outputs
Outputs from Magnetic Resonance in Medicine
#6,477
of 7,203 outputs
Outputs of similar age
#272,290
of 315,352 outputs
Outputs of similar age from Magnetic Resonance in Medicine
#71
of 124 outputs
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