Sci—Thur PM: Imaging — 03: A novel Čerenkov detector based on air‐spaced light guiding taper for megavoltage x‐ray imaging
Bibliographic record
Abstract
Electronic Portal Imaging Devices (EPIDs) have been used in radiation therapy and are still needed on linear accelerators (Linacs) equipped with kilovoltage cone beam CT (kV‐CBCT) or MRI systems. Recently a new concept of a high quantum efficiency (QE) Čerenkov Portal Imaging Device (CPID) for MV x‐ray imaging in radiation therapy was introduced. It relies on Čerenkov effect for x‐ray detection. The proposed design consisted 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. A weakness of such design is that too few Čerenkov light photons reach the AMFPI for each incident x‐ray and an AMFPI with an avalanche gain is required. In this work we propose to replace the optical fibers in the CPID with light guides without a cladding layer that are suspended in air. The air between the light guides takes on the role of the cladding layer found in a regular optical fiber. Since air has a significantly lower refractive index, a much superior light collection efficiency is achieved. Our Monte Carlo studies have shown that the modified new CPID has a QE more than an order of magnitude greater than that of current clinical systems and yet a spatial resolution similar to that of current flat‐panel based EPIDs. Furthermore it has been demonstrated that the new CPID does not require an avalanche gain in the AMFPI and is quantum noise limited at dose levels corresponding to a single Linac pulse.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".