One shot, one SoS: A real-time, single-shot global speed of sound estimator
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
• We devised the first experimentally validated single-shot global speed-of-sound (SoS) estimator for ultrasound imaging. • Our new algorithm can be readily coupled with an ultrasound imaging sequence to acquire SoS values in real-time. • Accurate SoS estimates with small mean signed difference were obtained in vitro (0.4 ± 6.5 m/s) and in vivo (3.8 ± 15.7 m/s). • This work serves well to advance the emerging use of SoS in quantitative tissue characterization. • This work also benefits other imaging processes that are influenced by SoS, such as beamforming and Doppler estimation. Speed of sound (SoS), or the propagation speed of acoustic waves through a medium, is an intrinsic property of human tissue and has emerged as a new biomarker in health diagnostics. Alas, no existing technique has practically demonstrated that the tissue SoS can be robustly measured from a single pulse-echo transmission with an imaging transducer, so incorporating SoS estimation into the ultrasound imaging pipeline remains technically challenging. In this paper, we propose a novel global SoS estimation algorithm that requires only a single steered plane wave transmission for operation. Our single-shot framework derives the SoS estimate by 1) calculating each pixel’s pre-beamformed sum of normalized autocorrelation coefficients (SNAC) derived from the time-delayed channel data ensemble for an assumed SoS; 2) constructing a loss metric that is defined as, for different SoS candidates, the negated total SNAC over different pixels; 3) finding the SoS with the minimum loss value. Our single-shot SoS estimator was implemented in real-time (50 ms processing time) on a portable ultrasound research scanner. It was tested in vitro using agar staircase phantoms (SoS range: 1508–1682 m/s) and in vivo using svelte human calves (SoS range: 1573–1589 m/s). All SoS estimates were validated with reference through-transmission measurements. Results show that our framework yielded accurate SoS estimates with a small mean signed difference (MSD) in vitro (0.4 ± 6.5 m/s) and in vivo (3.8 ± 15.7 m/s). When the framework was extended to a 10-angle multi-transmission sequence, its SoS estimation performance was further improved with a smaller MSD (0.2 ± 2.0 m/s). The advent of the proposed single-shot SoS estimator can help advance the emerging use of SoS in tissue characterization and improve other imaging processes that are influenced by SoS, such as beamforming and Doppler estimation.
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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 | 0.000 | 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 it