A Simulation of a Novel High Quantum Efficiency Scintillating Fiber Detector with Anti-scatter Properties for Megavoltage X-Ray Imaging
Bibliographic record
Abstract
To further develop a MV x-ray portal imaging device with high detection efficiency and adequate spatial resolution for image guided radiation therapy, the experimental results for a prototype detector were matched using Monte-Carlo software to then improve upon the design. The simulation and experiment were carried out using a 6 MV beam from a linear accelerator machine. An adequate match was obtained with the spatial resolution matching up to a MTF value of 0.2 and then diverging and the total signal registered in the central fiber was matched for field sizes ranging from 3 cm by 3 cm to 20 cm by 20 cm for 5 cm, 15 cm and 25 cm air gaps within 3%. The design was altered from a hexagonal array of round double cladded fibers to a square array of single cladded square fibers. The spatial resolution was improved from 0.242 lp mm-1 to 0.359 lp mm-1 at an MTF value of 0.5 from the original design to a square array of square fibers 0.5 mm wide separated by 0.25 mm of lead foil. With further optimization of the detector design it may be possible to increase spatial resolution for MV x-ray imaging while maintaining an adequate detection efficiency.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".