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Modeling Endovascular MRI Coil Coupling With Transmit RF Excitation

Overview of attention for article published in IEEE Transactions on Biomedical Engineering, March 2016
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Article details
Title
Modeling Endovascular MRI Coil Coupling With Transmit RF Excitation
Published in
IEEE Transactions on Biomedical Engineering, March 2016
DOI 10.1109/tbme.2016.2538279
Pubmed ID
Authors
Abstract

To model inductive coupling of endovascular coils with transmit RF excitation for selecting coils for MRI-guided interventions. Independent and computationally efficient FEM models are developed for the endovascular coil, cable, transmit excitation and imaging domain. Electromagnetic and circuit solvers are coupled to simulate net B1+ fields and induced currents and voltages. Our models are validated using the Bloch Siegert B1+ mapping sequence for a series-tuned multimode coil, capable of tracking, wireless visualization and high resolution endovascular imaging. Validation shows good agreement at 24, 28 and 34 μT background RF excitation within experimental limitations. Quantitative coil performance metrics agree with simulation. A parametric study demonstrates trade off in coil performance metrics when varying number of coil turns. Tracking, imaging and wireless marker multimode coil features and their integration is demonstrated in a pig study. Developed models for the multimode coil were successfully validated. Modeling for geometric optimization and coil selection serves as a precursor to time-consuming and expensive experiments. Specific applications demonstrated include parametric optimization, coil selection for a cardiac intervention and an animal imaging experiment. Our modular, adaptable and computationally efficient modeling approach enables rapid comparison, selection and optimization of inductively-coupled coils for MRI-guided interventions.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 4 21%
Student > Ph. D. Student 3 16%
Student > Master 2 11%
Student > Postgraduate 2 11%
Other 1 5%
Other 1 5%
Unknown 6 32%
Readers by discipline
Readers by discipline Count As %
Engineering 7 37%
Medicine and Dentistry 3 16%
Computer Science 1 5%
Energy 1 5%
Neuroscience 1 5%
Other 0 0%
Unknown 6 32%
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 03 May 2016.
All research outputs
#19,109,720
of 27,700,660 outputs
Outputs from IEEE Transactions on Biomedical Engineering
#4,301
of 4,839 outputs
Outputs of similar age
#196,657
of 317,205 outputs
Outputs of similar age from IEEE Transactions on Biomedical Engineering
#25
of 30 outputs
Altmetric has tracked 27,700,660 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,839 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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