A radiofrequency coil to facilitate <i>B</i> shimming and parallel imaging acceleration in three dimensions at 7 T
Bibliographic record
Abstract
A 15-channel transmit-receive (transceive) radiofrequency (RF) coil was developed to image the human brain at 7 T. A hybrid decoupling scheme was implemented that used both capacitive decoupling and the partial geometric overlapping of adjacent coil elements. The decoupling scheme allowed coil elements to be arrayed along all three Cartesian axes; this facilitated shimming of the transmit field, B₁⁺, and parallel imaging acceleration along the longitudinal direction in addition to the standard transverse directions. Each channel was independently controlled during imaging using a 16-channel console and a 16 × 1-kW RF amplifier-matrix. The mean isolation between all combinations of coil elements was 18 ± 7 dB. After B₁⁺ shimming, the standard deviation of the transmit field uniformity was 11% in an axial plane and 32% over the entire brain superior to the mid-cerebellum. Transmit uniformity was sufficient to acquire fast spin echo images of this region of the brain with a single B₁⁺ shim solution. Signal-to-noise ratio (SNR) maps showed higher SNR in the periphery vs center of the brain, and higher SNR in the occipital and temporal lobes vs the frontal lobe. Parallel imaging acceleration in a rostral-caudal oblique plane was demonstrated. The implication of the number of channels in a transmit-receive coil was discussed: it was determined that improvements in SNR and B₁⁺ shimming can be expected when using more than 15 independently controlled transmit-receive channels.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".