Beamforming and Imaging Approaches for Array-Based Dual-Frequency Acoustic Angiography
Bibliographic record
Abstract
Acoustic angiography (AA) using dual frequency (DF) ultrasound systems enables high-resolution and high-contrast imaging of the microvasculature within tissue. AA has been used to detect changes in vasculature due to cancerous tumours, and it has the potential to aid the evaluation of treatment outcomes. DF ultrasound imaging uses conventional frequency ultrasound transducers (~2-4 MHz, LF) on transmit (Tx), and high frequency (HF) transducers on receive (Rx) to detect higher order harmonics (~10-20 MHz) from microbubble contrast agents. In this paper, we show a DF array, with LF and HF arrays integrated within the probe head that overcomes limitations of the previously used single channel DF probes such as the limited focal depth. The integrated DF array has been connected to a configurable micro-US beamforming system to allow plane wave on Tx and parallel Rx in both HF and DF imaging modes. This work presents DF and HF imaging modes with plane wave imaging techniques to visualize a contrast-filled channel within a tissue-mimicking phantom.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".