Dual-modality flow phantom for ultrasound and optical flow measurements
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Bibliographic record
Abstract
Abstract As ultrasound-compatible flow phantoms are devised for performance testing and calibration, there is a practical need to obtain independent flow measurements for validation using a gold-standard technique such as particle image velocimetry (PIV). In this paper, we present the design of a new dual-modality flow phantom that allows ultrasound and PIV measurements to be simultaneously performed. Our phantom’s tissue mimicking material is based on a novel hydrogel formula that uses propylene glycol to lower the freezing temperature of an ultrasound-compatible poly(vinyl) alcohol cryogel and, in turn, maintain the solution’s optical transparency after thermocycling. The hydrogel’s optical attenuation {1.56 dB cm −1 with 95% confidence interval (CI) of [1.512 1.608]}, refractive index {1.337, CI: [1.340 1.333]}, acoustic attenuation {0.038 dB/(cm × MHz b ), CI: [0.0368 0.0403]; frequency dependent factor of 1.321, CI: [1.296 1.346]}, and speed of sound {1523.6 m s −1 , CI: [1523.8 1523.4]} were found to be suitable for PIV and ultrasound flow measurements. As an application demonstration, a bimodal flow phantom with spiral lumen was fabricated and used in simultaneous flow measurements with PIV and ultrasound color flow imaging (CFI). Velocity fields and profiles were compared between the two modalities under a constant flow rate (2.5 ml s −1 ). CFI was found to overestimate flow speed compared to the PIV measurements, with a 14%, 10%, and 6% difference between PIV and ultrasound for the 60°, 45°, and 30° angles measured. These results demonstrate the new phantom’s feasibility in enabling performance validation of ultrasound flow mapping tools.
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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 | 0.000 |
| 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