Detunable wireless Litzcage coil for human head MRI at 1.5 T
Bibliographic record
Abstract
Inductively coupled radiofrequency (RF) coils are an inexpensive and simple method to realize wireless RF coils in magnetic resonance imaging (MRI), which can significantly ease the MRI scan setup and improve patient comfort because they do not require bulky components such as cables, baluns, preamplifiers, and connectors. However, volume-type wireless coils are typically operated in transmit/receive mode because detuning such coils is much more challenging due to their complex structure and multiple resonant modes. Meanwhile, adding too many detuning circuits to a wireless coil would decrease the coil's quality factor, impair the signal-to-noise ratio, and increase the cost. In this work, we proposed, constructed, and tested a novel wireless volume coil based on the Litzcage design for 1.5-T head imaging. Being an inductively coupled coil, it has a much simpler structure, resulting in a lighter weight and less bulky design. Despite its simpler structure, it exhibits comparable imaging performance with a commercial receive array, providing an alternative to conventional wired coils with a high cost and complex structure. The unique figure-of-8 conductor pattern within the rungs ensures that the proposed wireless Litzcage can be efficiently detuned with minimal detuning circuits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".