Extending Reach Inside the MRI Bore: A 7-DOF, Low-Friction, Hydrostatic Teleoperator
Bibliographic record
Abstract
We present a hydrostatic teleoperator that provides physicians remote access inside the MRI bore and enables real-time MRI guided interventions such as liver biopsies. The device consists of a custom six-axis arm and a needle insertion end effector. The manipulator is passive and backdrivable with a near one-to-one mapping of motions and forces between the input and output. The six-axis arm translates and orients the needle during insertion and passively reflects respiratory motion while maintaining contact with the skin surface. Arm joints employ novel rotary rolling-diaphragms that provide stiff and low-friction rotational motion without the need for cables, belts, or gear mechanisms found in other solutions. We perform experiments to characterize the device's force and position tracking and demonstrate its functionality with path following tasks. Our results find a system roll-off frequency at 20Hz and that teleoperation tasks are performed comparably to holding the output directly. We motivate the need for force transparency in MRI guided biopsies with a user study in which five radiologists perform phantom membrane puncture biopsies using the needle insertion mechanism. The results indicate a 50% reduction in scans and a 14.5% decrease in membrane overshoot when force feedback is present.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".