Feasibility of Using Lateral Mode Coupling Method for a Large Scale Ultrasound Phased Array for Noninvasive Transcranial Therapy
Bibliographic record
Abstract
A hemispherical-focused, ultrasound phased array was designed and fabricated using 1372 cylindrical piezoelectric transducers that utilize lateral coupling for noninvasive transcranial therapy. The cylindrical transducers allowed the electrical impedance to be reduced by at least an order of magnitude, such that effective operation could be achieved without electronic matching circuits. In addition, the transducer elements generated the maximum acoustic average surface intensity of 27 W/cm(2). The array, driven at the low (306-kHz) or high frequency (840-kHz), achieved excellent focusing through an ex vivo human skull and an adequate beam steering range for clinical brain treatments. It could electronically steer the ultrasound beam over cylindrical volumes of 100-mm in diameter and 60-mm in height at 306 kHz, and 30-mm in diameter and 30-mm in height at 840 kHz. A scanning laser vibrometer was used to investigate the radial and length mode vibrations of the element. The maximum pressure amplitudes through the skull at the geometric focus were predicted to be 5.5 MPa at 306 kHz and 3.7 MPa at 840 kHz for RF power of 1 W on each element. This is the first study demonstrating the feasibility of using cylindrical transducer elements and lateral coupling in construction of ultrasound phased 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) | 0.000 | 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".