Needle Insertion Point and Orientation Optimization in Non-linear Tissue with Application to Brachytherapy
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a new method of optimizing the needle insertion point, heading and depth for needle insertion into deformable tissue. The goal is to minimize the distance between a number of specified targets and the needle. Assuming a rigid needle and a deformable tissue described by a finite element model, an iterative optimization method is proposed that uses the needle insertion simulation. At each iteration, the best fitted 3D line to the targets in the simulated deformed configuration is used as a candidate for the new insertion line in the next iteration. This method has been implemented in a prostate brachytherapy simulator to minimize seed misplacement errors. The targets are designed to lie on a straight line in the undeformed configuration inside the prostate. To increase the accuracy while simulating the prostate rotation, a non-linear model is used. The neo-Hookean material model is exploited to determine the effects of geometric and mechanical nonlinearities and compressibility effects. It is shown that the optimization algorithm converges in few iterations and decreases the targeting error effectively.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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