Monitoring Focused Ultrasound Thermal Therapy Using Synthetic Aperture Ultrasound Imaging With Decorrelated Compounding
Bibliographic record
Abstract
Decorrelated Compounding (DC) for synthetic aperture ultrasound reduces speckle in images, suggesting enhanced detectability of low-contrast thermal lesions produced by Focused Ultrasound (FUS). Ex vivo porcine tissue was imaged during FUS exposure to induce a lowcontrast thermal lesion and localized heating. Image quality was assessed using the Contrast-toNoise Ratio (CNR) and the speckle SNR (sSNR). DC imaging improves both the CNR and sSNR up to a factor of 9 in comparison to B-mode imaging. The feasibility of change in backscattered energy (CBE) thermometry with DC imaging was also investigated. Measured changes in signal and backscattered energy at the focal point yielded lower uncertainties and follow temperature profiles more closely when measured using DC imaging. These suggest that the DC method can measure subtle, temperature dependent tissue changes and can be used to monitor FUS thermal therapy.
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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 | 0.000 |
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".