Fourier Domain Depth Migration for Plane-Wave Ultrasound Imaging
Bibliographic record
Abstract
Plane-wave (PW) ultrasound imaging allows for ultrafast image acquisition rates, thus enabling new biomedical applications, such as ultrasound-based blood flow and tissue motion characterization. We propose two novel Fourier domain techniques for PW ultrasound image reconstruction that can be used as an alternative to conventional delay-and-sum beamforming. In particular, we show how to modify two classic algorithms used for geophysical data processing (namely, Stolt's and slant-stack depth migration under zero-offset constant-velocity assumptions), so that their new versions can be used for PW ultrasound data processing. To demonstrate the merits and limitations of our approach, we provide qualitative and quantitative comparisons with other Fourier domain methods reported in the ultrasound literature. Our evaluation results are based on the image resolution, contrast, and similarity metrics obtained for several public-domain experimental benchmark data sets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".