Towards high frame rate cardiac ultrasonography - a circular wave imaging approach
Bibliographic record
Abstract
Analysis and quantification of both intracardiac blood flow and myocardial motion by Doppler ultrasound (US) are of major interest to early detect heart failure. Furthermore these medical examinations are becoming part of daily clinical setups. Although noninvasive measures are yielded by conventional US Doppler, these are incomplete since only the velocity components along the US beam direction are captured. In addition, because one usually needs to cover a large sector in cardiac imaging, frame rates (typically <; 50 fps) offered by standard focused US are generally too low to fully describe the intracavitary blood flow and tissue motion. For the same last reason, alternate techniques such as speckle tracking and/or echo-PIV (particle image velocimetry) are also currently limited by a reduced frame rate. The objective of this in vitro study was to demonstrate the capability of ultrafast circular wave imaging to provide accurate time-resolved vector flow mapping over a wide deep sector scan. Circular wave imaging was chosen in the context of potential cardiac applications, where wide regions of interest (ROI) are required but only small intercostal acoustic windows are available.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".