SU‐E‐T‐53: A New Method for Characterizing the Stability of the Treatment Couch Isocentre
Bibliographic record
Abstract
Purpose: In this work we propose a new method for characterizing the accuracy of a linear accelerator treatment couch's isocentre. This is accomplished by a direct determination of the coordinates of the center of rotation as a function of rotation angle. Methods: A phantom consisting of five metallic BBs arranged in a plane was constructed. The phantom was positioned on the treatment couch such that the plane of the BBs was horizontal, while the central BB was aligned with the linac isocentre. With the gantry in the vertical position, the couch was rotated through its full range of rotation while EPID images were acquired every 10 degrees. For each rotation angle, the coordinates of the rotation center were calculated from the displacement of each of the four off‐center BBs identified on a pair of EPID images taken between successive rotations. The accuracy of the couch isocentre was evaluated from the distribution of the rotation center coordinates. Our results were compared with film based star‐shot measurements of the couch isocentre. Results: The measured couch center of rotation consisted of a cloud of points clustered around the linac isocentre within < 0.7 mm distance. The deviations of these points from the linac isocentre were in the range of 0.01 to 0.20 mm in the cross‐plane direction, and 0.10 to 0.61 mm in the in‐plane direction, with mean values of 0.09 mm and 0.32 mm. These results were consistent with the results obtained from the star‐shot method. Conclusion: A new method for determining the location and accuracy of the couch center of rotation has been successfully implemented. This method gives explicit values of the location and the stability of the couch isocentre, and it can be extended to gantry and collimator rotations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".