Path Planning with RRT*M Algorithm in Simulated Human Respiratory Environment
Bibliographic record
Abstract
Image-guided percutaneous insertion is widely applied in lung biopsy surgeries.Traditional procedure used rigid needle, which may lead to post-operation complications such as pneumothorax and hemothorax.Recent research have investigated the application of curvature-controllable steerable bevel-tip needle with pre-surgery path planning to overcome this problem.This work focuses on improving the RRT* algorithm (in terms of path length, search time and redundant random nodes) for the pre-operation path planning based on a constrained search environment.An RRT*M algorithm is proposed via probability distribution of the generation of random nodes around the ideal path connecting the start and goal points within a constraint region while avoiding the obstacles in the simulated human respiratory system.The performance of the proposed algorithm is compared with informed RRT* algorithm based on a similar 2D environment.The result indicated the potential of the proposed algorithm for lung biopsy path planning in a 3D virtual environment based on the human anatomy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".