Needle Insertion Parameter Optimization for Brachytherapy
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new needle path planning method for the insertion of rigid needles into deformable tissue. The needle insertion point, needle heading, and needle depth are optimized by minimizing the distance between a rigid needle and a number of targets in the tissue. The optimization method is based on iterative simulations performed using a tissue finite element model. At each iteration, the best 3-D line fitted to the displaced targets in the deformed tissue is used as a candidate for a new insertion line. First, this method is implemented in a prostate brachytherapy simulator under different boundary conditions to minimize the targeting error. It is shown that the optimization method converges in a few iterations and decreases the seed misplacement error to less than the needle diameter. Second, the efficacy of the optimization algorithm is verified by optimizing the insertion parameters for a brachytherapy needle before insertion into a prostate tissue phantom. The elastic properties of the phantom and the needle-tissue interaction parameters were identified in an independent experiment. The optimization algorithm is effective in decreasing the targeting error.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it