Scatter corrections for cone beam optical CT
Bibliographic record
Abstract
Cone beam optical computed tomography (OptCT) employing the VISTA scanner (Modus Medical, London, ON) has been shown to have significant promise for fast, three dimensional imaging of polymer gel dosimeters. One distinct challenge with this approach arises from the combination of the cone beam geometry, a diffuse light source, and the scattering polymer gel media, which all contribute scatter signal that perturbs the accuracy of the scanner. Beam stop array (BSA), beam pass array (BPA) and anti-scatter polarizer correction methodologies have been employed to remove scatter signal from OptCT data. These approaches are investigated through the use of well-characterized phantom scattering solutions and irradiated polymer gel dosimeters. BSA corrected scatter solutions show good agreement in attenuation coefficient with the optically absorbing dye solutions, with considerable reduction of scatter-induced cupping artifact at high scattering concentrations. The application of BSA scatter corrections to a polymer gel dosimeter lead to an overall improvement in the number of pixel satisfying the (3%, 3mm) gamma value criteria from 7.8% to 0.15%.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".