A workspace‐orientated needle‐guiding robot for 3T MRI‐guided transperineal prostate intervention: evaluation of in‐bore workspace and MRI compatibility
Bibliographic record
Abstract
BACKGROUND: Magnetic resonance imaging (MRI)-guided prostate interventions have been introduced to enhance the cancer detection. For accurate needle positioning, in-bore-operated robotic systems have been developed and optimal use of the confined in-bore space become a critical engineering challenge. METHODS: As preliminary evaluation of our prostate intervention robot, we conducted a workspace design analysis, using a new evaluation method that we developed for in-bore-operated robots for transperineal prostate interventions, and an MRI compatibility study. RESULTS: The workspace analysis resulted in the effective workspace (VW ) of 0.32, which is greater than that of our early prototype, despite the current robot being ca. 50% larger than the early prototype in sectional space. The MRI compatibility study resulted in < 15% signal:noise ratio (SNR) reduction. CONCLUSIONS: The new workspace evaluation method quantifies the workspace utilization of the in-bore-operated robots for MRI-guided transperineal prostate interventions, providing a useful tool for evaluation and new robot design. The robot creates insignificant electromagnetic noise during typical prostate imaging sequences.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".