MRI-Compatible Pneumatic Robot for Transperineal Prostate Needle Placement
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of prostate and surrounding tissue, thus granting potential to be a superior medical imaging modality for guiding and monitoring prostatic interventions. However, the benefits cannot be readily harnessed for interventional procedures due to difficulties that surround the use of high-field (1.5T or greater) MRI. The inability to use conventional mechatronics and the confined physical space makes it extremely challenging to access the patient. We have designed a robotic assistant system that overcomes these difficulties and promises safe and reliable intraprostatic needle placement inside closed high-field MRI scanners. MRI compatibility of the robot has been evaluated under 3T MRI using standard prostate imaging sequences and average SNR loss is limited to 5%. Needle alignment accuracy of the robot under servo pneumatic control is better than 0.94 mm rms per axis. The complete system workflow has been evaluated in phantom studies with accurate visualization and targeting of five out of five 1 cm targets. The paper explains the robot mechanism and controller design, the system integration, and presents results of preliminary evaluation of the system.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".