Megavoltage X-Ray Imaging Based on Cerenkov Effect: A New Application of Optical Fibres to Radiation Therapy
Bibliographic record
Abstract
A Monte Carlo simulation was used to study imaging and dosimetric characteristics of a novel design of megavoltage (MV) X-ray detectors for radiotherapy applications. The new design uses Cerenkov effect to convert X-ray energy absorbed in optical fibres into light for MV X-ray imaging. The proposed detector consists of a matrix of optical fibres aligned with the incident X rays and coupled to an active matrix flat-panel imager (AMFPI) for image readout. Properties, such as modulation transfer function, detection quantum efficiency (DQE), and energy response of the detector, were investigated. It has been shown that the proposed detector can have a zero-frequency DQE more than an order of magnitude higher than that of current electronic portal imaging device (EPID) systems and yet a spatial resolution comparable to that of video-based EPIDs. The proposed detector is also less sensitive to scattered X rays from patients than current EPIDs.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".