Geometrically accurate real-time volumetric visualization of the middle ear using optical coherence tomography
Bibliographic record
Abstract
We introduce a novel system for geometrically accurate, continuous, live, volumetric middle ear optical coherence tomography imaging over a 10.9 m m ×30 ∘ ×30 ∘ field of view (FOV) from a handheld imaging probe. The system employs a discretized spiral scanning (DC-SC) pattern to rapidly collect volumetric data and applies real-time scan conversion and lateral angular distortion correction to reduce geometric inaccuracies to below the system’s lateral resolution over 92% of the FOV. We validate the geometric accuracy of the resulting images through comparison with co-registered micro-computed tomography (micro-CT) volumes of a phantom target and a cadaveric middle ear. The system’s real-time volumetric imaging capabilities are assessed by imaging the ear of a healthy subject while performing dynamic pressurization of the middle ear in a Valsalva maneuver.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".