Poster — Thur Eve — 77: Coordinate transformation from DICOM to DOSXYZnrc
Bibliographic record
Abstract
DICOM format is the de facto standard for communications between therapeutic and diagnostic modalities. A plan generated by a treatment planning system (TPS) is often exported to DICOM format. BEAMnrc/DOSXYZnrc is a widely used Monte Carlo (MC) package for beam and dose simulations in radiotherapy. It has its own definition for beam orientation, which is not in compliance with the one defined in DICOM standard. Dose simulations using TPS generated plans require transformation of beam orientations to DOSXYZnrc coordinate system (c.s.) after extracting the necessary parameters from DICOM RP files. The transformation is nontrivial. There have been two studies for the coordinate transformations. The transformation equation sets derived have been helpful to BEAMnrc/DOSXYZnrc users. However, both the transformation equation sets are complex mathematically and not easy to program. In this study, we derive a new set of transformation equations, which are more compact, better understandable, and easier for computational implementation. The derivation of polar angle θ and azimuthal angle φ is similar to the existing studies by applying a series of rotations to a vector in DICOM patient c.s. The derivation of beam rotation Φcol for DOSXYZnrc, however, is different. It is obtained by a direct combination of the actual collimator rotation with the projection of the couch rotation to the collimator rotating plane. Verification of the transformation has been performed using clinical plans created with Eclipse. The comparison between Eclipse and MC results show exact geometrical agreement for field placements, together with good agreement in dose 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.145 | 0.088 |
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".