Golay Pulse Encoding for Microbubble Contrast Imaging in Ultrasound
Bibliographic record
Abstract
We present a technique that uses Golay phase encoding, pulse inversion, and amplitude modulation (GPIAM) for microbubble contrast agent imaging with ultrasound. This technique improves the contrast-to-tissue ratio (CTR) by increasing the time-bandwidth product of the insonating waveforms. A nonlinear pulse compression algorithm is used to compress the signal energy upon receive. A 6.5-dB improvement in CTR was observed using an 8-chip GPIAM sequence compared to a conventional pulse-inversion amplitude-modulation sequence. The CTR improvement comes at the cost of a reduction in frame rate: GPIAM coding uses four input pulses whereas most contrast imaging sequences require two or three pulses. Our results showed that the microbubble response can be phase encoded and subsequently compressed using a nonlinear matched-filtering algorithm, in order to enhance the signal from the contrast agent, while maintaining resolution and suppressing the tissue signal.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".