Methods and Analysis of 3D Shape Unfolding and Folding for Radiotherapy
Bibliographic record
Abstract
A sheet of material called bolus is commonly used in the high-energy radiotherapy to treat tumors near the skin surface of patients for a desired dose distribution. The existing method of bolus shaping is a manual process to cut the material into 2D shapes and then wrap them to fit the targeted body surface in clinic. This method cannot cover the bolus on some irregular surfaces such as knee, nose and elbow precisely. The inaccurate coverage will generate air gaps between the bolus and skin. An unfolding method for bolus shaping is introduced in this paper to reduce the air gaps. The shaping process is achieved by planning unfolding strategy to overcome limitations of existing software tools. A case study of bolus shaping for human nose is presented to examine the proposed shaping process. The shaping process includes the surface scanning to obtain point cloud data, 3D surface forming, segmentation and unfolding of the surface. The solution is verified by comparing the 3D model surface and wrapped shape of unfolded patches.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".