4-D x 3-D ultrasound: real-time scan conversion, filtering, and display of displacement vectors with a motorized curvilinear transducer
Bibliographic record
Abstract
Recent research in the field of elastography has sought to expand displacement tracking to three dimensions. Once the 3-D volumes of displacement data have been obtained, they must be scan converted so that further processing, such as inversion methods to obtain tissue elasticity, can take place in Cartesian coordinates. This paper details an efficient and geometrically accurate algorithm to scan convert 3-D volumes of displacement vectors obtained from a motorized sector transducer. The proposed algorithm utilizes the physical scan geometry to convert the 3-D volumes of displacement data to both Cartesian coordinates and Cartesian displacements. Spatially varying filters are also proposed to prevent aliasing while minimizing data loss. Validation of the system has shown the algorithm to be correct to floating point precision, and the 3-D scan conversion and filtering can be performed faster than the native rate of data acquisition for the motorized transducer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".