TU‐C‐108‐02: Novel Full 3D Water‐Equivalent Dosimetry Technique Using a Single Light‐Field Camera for Photons, Electrons and Ion‐Beams Dosimetry
Bibliographic record
Abstract
Purpose: Using an array of micro‐lenses coupled with its active sensor, a light‐field camera samples the incoming optical photons in both the spatial and angular domain. This work presents the proof‐of‐concept and experimental validation of a 3D dosimeter based on the reconstruction of the light pattern emitted from a plastic scintillator volume and recorded using a light‐field camera. Using a single, fixed camera device, this technology enables real‐time, multi‐plane experimental measurement of static and dynamic radiotherapy delivery. Method: A Raytrix R5 light‐field camera was used to image a 10×10×10cm3 EJ‐260 plastic scintillator immersed in a water tank and irradiated with both square field and small MLC segments on a Clinac iX linear accelerator. The 3D light distribution emitted by the scintillator volume was reconstructed at a 5mm resolution in all dimensions by backprojecting the light collected by each pixel of the light‐field camera using a total variation minimization iterative reconstruction algorithm. Results: Signal contamination by Cerenkov emission was evaluated to less than 0.5% of the collected scintillation light for all field investigated, and as such Cerenkov light filtration was deemed unnecessary. Light‐field acquisition rate of at least 1 frame per second was achieved by the camera at a 600MU/min dose rate. The absolute dose difference between the reconstructed 3D dose and the expected dose calculated using the treatment planning software Pinnacle3 was on average below 3% for square fields and 5% for MLC segments in the high dose, low gradient region of each acquired field. Conclusions: Millimeter resolution dosimetry over an entire 3D volume is achievable in real‐time using a single light‐field camera. Because no moving parts are required in the dosimeter, the incident dose distribution can be acquired as a function of time, thus enabling the validation of static and dynamic radiation delivery with photons, electrons and ions.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 0.001 |
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".