Phased array techniques for multiple focus synthesis in transcranial focused ultrasound
Bibliographic record
Abstract
Recent clinical successes of transcranial focused ultrasound have occurred in the treatments of essential tremor, neuropathic pain, and Parkinson's disease, among others. We will present results of an investigation into the synthesis of multiple foci using iterative steering through multiple points and phased array controls for multiple focus acoustic patterns. In this numerical study, exported computed tomography (CT) imaging data of the skull was segmented and positioned inside a hemispherical phased array. A combination of full-wave and ray acoustic models were used to simulate the calculation of phased array controls and the resultant acoustic field. Using techniques from previous work on simultaneous multiple focus synthesis and rapidly steered foci in homogeneous media, it is shown that it is possible to elevate the temperature in the brain to therapeutic hyperthermia levels. In addition, potential applications for microbubble-mediated therapies using these techniques are discussed. These results indicate that transcranial hyperthermia over large volumes using focused ultrasound is possible and may have applications to future thermal therapies.
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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) | 0.002 | 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 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".