4K-3 A Combined Array for Localized Harmonic Imaging: A Simulation Study of Feasibility of Motion Detection
Bibliographic record
Abstract
In this study, feasibility of different pulse-echo fields to detect ultrasound radiation force induced displacements in soft tissue have been investigated. We used a linear phased array that consisted of 128 geometrically focused elements having the focal depth of 40 mm. The vibration distributions caused by an amplitude-modulated radiation force field induced in a homogeneous soft tissue block by the focused ultrasound beam from the phased array were simulated. Then part of the array was used to emit ultrasound pulses to detect the tissue motion. Properties of the emitted pulses were considered at the geometric focal depth using 2-32 elements. The elements used in the pulse-echo mode were driven at frequencies 5.5 MHz or 7.7 MHz. The vibration distribution was pulse-echo imaged using 2-16 elements so that the place of the tracking elements in the transducer was moved across the centre axis of the transducer. The simulated echo signals were computed using FIELD II program and the cross-correlation of these rf-signals was used in the displacement analyze. The results indicate that the displacement amplitude and distribution can be detected using pulse-echo imaging. As a conclusion it was shown that it should be possible to use a linear phased array for both induction of the tissue motion and its detection
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".