Design of a tracked ultrasound calibration phantom made of LEGO bricks
Bibliographic record
Abstract
PURPOSE: Spatial calibration of tracked ultrasound systems is commonly performed using precisely fabricated phantoms. Machining or 3D printing has relatively high cost and not easily available. Moreover, the possibilities for modifying the phantoms are very limited. Our goal was to find a method to construct a calibration phantom from affordable, widely available components, which can be built in short time, can be easily modified, and provides comparable accuracy to the existing solutions. METHODS: We designed an N-wire calibration phantom made of LEGO® bricks. To affirm the phantom’s reproducibility and build time, ten builds were done by first-time users. The phantoms were used for a tracked ultrasound calibration by an experienced user. The success of each user’s build was determined by the lowest root mean square (RMS) wire reprojection error of three calibrations. The accuracy and variance of calibrations were evaluated for the calibrations produced for various tracked ultrasound probes. The proposed model was compared to two of the currently available phantom models for both electromagnetic and optical tracking. RESULTS: The phantom was successfully built by all ten first-time users in an average time of 18.8 minutes. It cost approximately $10 CAD for the required LEGO® bricks and averaged a 0.69mm of error in the calibration reproducibility for ultrasound calibrations. It is one third the cost of similar 3D printed phantoms and takes much less time to build. The proposed phantom’s image reprojections were 0.13mm more erroneous than those of the highest performing current phantom model The average standard deviation of multiple 3D image reprojections differed by 0.05mm between the phantoms CONCLUSION: It was found that the phantom could be built in less time, was one third the cost, compared to similar 3D printed models. The proposed phantom was found to be capable of producing equivalent calibrations to 3D printed phantoms.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".