A Novel Manipulator for 3D Ultrasound Guided Percutaneous Needle Insertion
Bibliographic record
Abstract
The prostate is a small exocrine gland in men responsible for production of the liquid component of the seminal fluid. In North America, prostate cancer accounts for over 300,000 new cases and 40,000 deaths each year and it is the second leading cause of cancer death in men. Low-dose Rate (LDR) brachytherapy is gaining interest as a viable treatment option for prostate cancer due to its low side effects and high benefits. The present manual approach for brachytherapy needle insertion and the inherent flexibility of the needles make it extremely difficult to achieve accurate and consistent dosimetry. In this paper, we present a new 5 degrees-of-freedom (DOF) manipulator capable of performing percutaneous needle insertion. The manipulator can perform orientation, insertion and rotation of the needle and linear motion of the plunger to drop radioactive seeds at targeted locations. The manipulator is an integral part of a system utilizing a mechanically rotated side-fire transducer to create 3D ultrasound images of the organ and utilizing 3D SLICER software to visualize those images. Experiments conducted in agar phantoms reveal an average RMS targeting error of 1.45mm at an average insertion depth of 75.78mm proving the feasibility and efficacy of the proposed robotic system for percutaneous needle insertion.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".