Analysis of circumferential shielding as a methodto decouple radiofrequency coils for high‐field MRI
Bibliographic record
Abstract
Abstract Reducing the impact of mutual coupling in magnetic resonance imaging (MRI) radiofrequency (RF) coil transmit/receive arrays constitutes a serious design challenge. Recently, it has been shown that mutual coupling in such arrays can be significantly reduced by circumferentially shielding the individual array elements. For such a decoupling method to be optimized and readily incorporated into future array designs, comprehensive analysis of the shield's effect on overall element and array performance is required. This study is focused on methodically analyzing this decoupling method to determine the effect of shielding geometry on overall coil performance in high‐field MRI. To this end, experiments on a 7‐Tesla MRI system, as well as full‐wave electromagnetic simulations, were performed and performance metrics, such as Q ‐factor, power efficiency, transmit power, signal‐to‐noise ratio (SNR), and specific absorption rate (SAR), were investigated for different coil/shield configurations. Differences in the geometry of a RF coil and its respective shield resulted in an increase in peak SNR of up to 40% compared to an unshielded coil. This was concurrent with a 2–4 dB reduction in the required transmit power to produce a given flip angle and a 25% reduction in peak local SAR compared to the unshielded coil. Coupling between adjacent loaded coils was strongly influenced by the coil/shield geometry and ranged from –6.5 to –22.1 dB. Based upon the analysis presented herein, example coil‐array designs are provided and have been optimized for either peripheral or whole‐brain imaging. © 2013 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 43B:11–21, 2013
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".