A new method to perform quantitative measurement of bronchoscopic images
Bibliographic record
Abstract
Bronchoscopy is a commonly used clinical tool that provides a direct image of the bronchial lumen. However, bronchoscopy has seen little use as a quantitative measurement tool, mainly because of the wide-angle lens which distorts the image. The present authors have tested the ability of numerical algorithms and commercial software to correct for this distortion. Test objects of known size were imaged with four different bronchoscopes. Commercial image analysis software was used to measure the size of features in the images before and after applying distortion correction algorithms. The technique was then applied by measuring airway narrowing in anaesthetized pigs during vagal stimulation. Without correction, object size near the edge of the field of view is underestimated by approximately 40%. The error in measured diameter of concentric circles was dependent on the radius of the circle, increasing to 25% for circles occupying 90% of the field. Third order polynomial functions were required to correct these errors. After correction, errors were independent of object size or location in the image. Correction for lens distortion was independent of the distance between bronchoscope and object. The authors conclude that modern image processing software can correct for the distortion produced by wide-angle bronchoscope lenses.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".