SU-E-T-51: Characterization of a Novel CCD Camera Based Imaging System for Radiochromic Film Dosimetry
Bibliographic record
Abstract
Purpose: In this paper we present work to further develop and characterize a novel method of reading radiochromic film. The technique is benchmarked against imaging on a clinically used Epson 10000XL scanner, using well characterized standard dose deliveries and patient IMRT QA results. Methods: A purpose-built CCD camera-based film digitizer was designed and prototyped with Modus Medical (London, Ontario). The system consists of a camera mounted above a LED lightbox, interfaced with computer image acquisition software. The system was based on components of the Vista optical CT scanner (Modus Medical Devices Inc.) and looks to improve on the flat-bed scanner based dosimetry system, which suffer from film orientation dependence and non-uniform scanner sensitivity. Various characteristics imaging system performance were measured including: dependence on camera aperture size, spatial resolution, light scatter contamination, lightbox temperature variation effects, and signal-to-noise ratio (SNR). Dose readout accuracy has also been determined using films that have been imaged using white-light and colour lightbox illumination system. Results are compared with readout using the Epson scanner. Results: The new system provides fast, orientation independent readout of radiochromic film. High resolution (0.25 mm x 0.25 mm pixel size) and high signal-to-noise ratio (SNR = 280 for 230 cGy, 10x10 cm square field) images are obtained in 6.7 seconds, averaging 100 frames. A warm-up time of at least one hour stabilizes light output and eliminates temperature effects. The readout of all test films agree well (to within 1% dose difference over most of the film) to the dose determined by other approaches. Conclusion: This new imaging technique shows good promise to simplify and improve on existing film dosimetry readout. Further development towards a commercial system is currently underway with Modus Medical. Research funding support provided by the Canadian Institutes of Health Research (CIHR)
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".