High Intensity Focused Ultrasound (HIFU) Thermal Lesion Detection Using Local Harmonic Imaging
Bibliographic record
Abstract
Local Harmonic Imaging (LHI) is an ultrasound-based method that can detect HIFU thermal lesions. This technique relies on the delivery of an acoustic radiation force to induce localized harmonic oscillations (LHO). LHO are tracked using high frame rate ultrasound imaging. In this study, it was hypothesized that the LHO amplitude for HIFU coagulated tissue is smaller than the LHO amplitude for normal tissue due to changes in the Young’s modulus. LHO amplitudes at three tissue stages were compared in porcine muscle tissue (normal: 6.53± 0.68 µm, 2 minutes HIFU: 5.01± 0.88 µm, and 4 minutes HIFU: 2.96± 0.59 µm). The Young’s moduli at these tissue stages were 11.28± 1.57 kPa, 24.21± 2.66 kPa, and 40.38± 4.38 kPa, respectively. It was concluded that the decrease in the LHO amplitude is proportional to the increase in Young’s modulus. Additionally, a theoretical model that represents the LHI technique was developed and validated.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".