Single wall closed-form differential ultrasound calibration
Bibliographic record
Abstract
In freehand 3D ultrasound, images are acquired while the position of the transducer is recorded with a tracking device. Calibration is essential in this technique to find the transformation from the image coordinates to the reference coordinate system. The single wall technique is a common calibration method because a simple plane phantom is used. Despite its advantages, such as ease of phantom construction and image analysis, this method requires large number of images to converge to the solution. One reason is a lack of a closed-form solution. Also, the technique uses slightly illconditioned sets of equations with a high condition number due to limited range of scanning motions that produce clear images of the plane. Here, a novel closed-form formulation has been proposed for the single wall calibration technique. Also, differential measurements of the plane image are used instead of absolute plane detection to improve accuracy. The closed-form solution leads to more accurate and robust results while providing an insight into understanding error propagation and finding the optimal set of transducer poses. Results have been compared to the conventional single wall technique. A residual error of 0.14 mm is achieved for the proposed method compared to 0.91 mm in the conventional approach.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".