Transmit/receive radiofrequency coil with individually shielded elements
Bibliographic record
Abstract
A novel method for decoupling coil elements of transmit/receive (transceive) arrays is reported. Each element of a coil array is shielded both concentrically and radially to reduce the magnetic flux linkage between neighboring coils; this substantially reduces the mutual inductance between coil elements and allows them to behave independently. A six-channel transceive coil was developed using this decoupling scheme and compared with two conventional decoupling schemes: the partial overlapping of adjacent elements and capacitive decoupling. The radiofrequency coils were designed to image the human head and were tested on a 7-T Varian scanner. The decoupling, transmit uniformity, transmit efficiency, signal-to-noise ratio, and geometry factors were compared between coils. The individually shielded coil achieved higher minimum isolation between elements (2.7-4.0 dB) and lower geometry factors (2-14%) than the overlapped and capacitively decoupled coils, while showing a reduction in transmit efficiency (2.8-5.9 dB) and signal-to-noise ratio (up to 34%). No difference was found in the power absorbed by the sample during a 90° radiofrequency pulse. The inset distance of coil elements within their shields was then reduced, resulting in significant improvement of the transmit efficiency (1.3 dB) and signal-to-noise ratio (28%). The greatest asset of this decoupling method lies in its versatility: transceive coils can be created with elements of arbitrary shape, size, location, and resonant frequency to produce three-dimensional conformal arrays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".