High-Frame Rate 3D-Synthetic Transmit Aperture Imaging with a Reduced Number of Measurement Channels
Bibliographic record
Abstract
This paper presents a high-frame rate, 3D synthetic transmit aperture system combined with a micro-beamforming technique to reduce the number of measurement channels M (the product of number of transmissions, nT, and the number of receiving channels in each transmission, nR). Adjacent elements were combined along both the lateral and the elevational direction into groups by applying proper delays in transmission and receiving to focus the beams at a specific region of interest. After the M channels of RF data were acquired, the frequency-domain spatial response function was used to reconstruct the ultrasound images. We have demonstrated that using this approach with a 9-fold reduction in transmission events and 49-fold reduction in receiving channels can achieve the comparable image quality with standard synthetic transmit aperture using a full array. The approach may help in realizing clinical applications of real-time 3D ultrasound imaging technology using large arrays.
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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 | 0.001 | 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 | 0.000 | 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".