Poster — Thur Eve — 04: The Line Spread Function Measurement of a Novel Transmission Detector
Bibliographic record
Abstract
Measurement‐based dose verification of planned intensity modulated radiotherapy (IMRT) fields requires a detector with good spatial resolution. A novel, transmission detector array has been recently developed by IBA Dosimetry (Germany) as an IMRT quality assurance tool. To characterize the detector system performance for verification of IMRT fluence, the line spread function (LSF) of a single ion chamber in the detector in a clinical 6 MV photon beam was measured with a narrow slit of width 0.25 mm. The LSF of the detector was obtained by laterally translating it in 0.5 mm steps underneath the slit, from the center to 16 mm distance from the center in the cross‐plane direction. The measured signal was corrected for background and leakage. The FWHM of the LSF for the single chamber was found to be 4.2 mm, which is comparable to the chamber size of 3.8 mm. The MTF of the detector system is a sinc function and with a first zero crossing of the MTF at spatial frequency of 0.25 lp/mm. This compares well to the value of 0.15 lp/mm found for the PTW (Germany) 2D‐ARRAY type 10024, also used for dose verification of IMRT fluence. We have successfully measured the LSF for a new novel transmission detector using a narrow slit method and a clinical 6MV photon beam. The transmission detector was found to have a better first zero crossing of the MTF compared to the 2D‐ARRAY type 10024. Research partly sponsored by IBA Dosimetry.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".