Unified Calibration Technique for Augmented-Reality Ultrasound-Guided Interventions
Bibliographic record
Abstract
Accurate spatial calibration for mobile imaging modality is the essential and enabling technology for augmented-reality based surgical navigation systems. Despite years of research, spatial calibration for surgical camera and freehand ultrasound remains areas of active research. In this paper, we present a unified spatial calibration framework for ultrasound probe calibration and camera hand-eye calibration using the same mathematical principle. By treating spatial calibration as a registration problem between paired points and lines, our framework provides i) efficient solutions with guaranteed convergence properties, and ii) based on error propagation model, a set of heuristic rules for fiducial placements that leads to accurate calibration consistently. Monte Carlo simulation demonstrated that accuracy camera hand-eye calibration (≈ 5 pixel) is possible with the Microsoft HoloLens 2 using as few as 6 fiducial measurements, and accurate ultrasound probe calibration can be consistently obtained using as few as 12 fiducial measurements.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".