An 8‐element Tx/Rx array utilizing MEMS detuning combined with 6 Rx loops for <sup>19</sup>F and <sup>1</sup>H lung imaging at 1.5T
Bibliographic record
Abstract
Purpose To firstly improve the attainable image SNR of 19 F and 1 H C 3 F 8 lung imaging at 1.5 tesla using an 8‐element transmit/receive (Tx/Rx) flexible vest array combined with a 6‐element Rx‐only array, and to secondly evaluate microelectromechanical systems for switching the array elements between the 2 resonant frequencies. Methods The Tx efficiency and homogeneity of the 8‐element array were measured and simulated for 1 H imaging in a cylindrical phantom and then evaluated for in vivo 19 F/ 1 H imaging. The added improvement provided by the 6‐element Rx‐only array was quantified through simulation and measurement and compared to the ultimate SNR. It was verified through the measurement of isolation that microelectromechanical systems switches provided broadband isolation of Tx/Rx circuitry such that the 19 F tuned Tx/Rx array could be effectively used for both 19 F and 1 H nuclei. Results For 1 H imaging, the measured Tx efficiency/homogeneity (mean ± percent SD; ) was comparable to that simulated ( ). The 6 additional Rx‐only loops increased the mean Rx sensitivity when compared to the 8‐element array by a factor of 1.41× and 1.45× in simulation and measurement, respectively. In regions central to the thorax, the simulated SNR of the 14‐element array achieves ≥70% of the ultimate SNR when including noise from the matching circuits and preamplifiers. A measured microelectromechanical systems switching speed of 12 µs and added minimum 22 dB of isolation between Tx and Rx were sufficient for Tx/Rx switching in this application. Conclusion The described single‐tuned array driven at 19 F and 1 H, utilizing microelectromechanical systems technology, provides excellent results for 19 F and 1 H dual‐nuclear lung ventilation imaging.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".