Repeatable calibration of Hounsfield units to mineral density and effect of scanning medium
Bibliographic record
Abstract
Computed tomography (CT) is being utilized in orthopaedics and related research to estimate bone strength. These applications benefit from calibration of Hounsfield units to mineral density typical of long bone, up to $1750mg/cm^3$ . This study describes a method for establishing repeatable calibration of Hounsfield units to density, and determines the effects of imaging medium on calibration accuracy. Four hydroxyapatite standards were imaged in air on 7 occasions over 19 weeks using a helical multi-slice CT scanner. Each standard was scanned 5 times in different media: porcine soft tissue, water, and air. Calibrated densities were highly repeatable (CV<3.5%). No difference in density was observed between water and soft tissue conditions (p>0.08). This work provides a model for determining repeatable scanner-specific density calibration, demonstrates that the linear relationship between Hounsfield units and density extends to values typical of cortical bone, and supports the practice of imaging calibration standards in an environment similar to that of the target bone.
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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 | 0.005 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".