Fluence profiles and energy spectral distributions of 100, 110, and 125 kVp photon beams: results of Monte Carlo simulations for a Varian OBI 1.4 CBCT
Bibliographic record
Abstract
Cone Beam Computed Tomography (CBCT) imaging for daily patient localization has gained enormous popularity as one of Image Guided Radiation Therapy (IGRT) methods in recent years. This is largerly due to the need of higher precision and accuracy in conformal beam delivery technique which is known as Intensity Modulated Radiation Therapy (IMRT). The success of this IMRT method is mainly determined by the treatment planning systems. The aim of this research is to provide detailed characteristics of incident photon beams for different beam energies from a Varian OBI 1.4 CBCT. The detailed characteristics consists of energy spectral distributions and fluence profiles. This information is critical to the future development of accurate treatment planning systems. BEAMnrc as one of EGSnrc Monte Carlo user code, has been used to simulate 100, 110, and 125 kVp photon beams from x-ray tube of a Varian OBI 1.4 CBCT. The details of each particle's complete history including where it has been and where it has interacted is stored in a phase space (phsp) data file. The phsp files are analyzed to obtain fluence profiles and energy spectral distributions.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".