Minimization of needle deflection in robot‐assisted percutaneous therapy
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Needle deflection and tissue deformation are two problems encountered during needle insertion into soft, non-homogeneous tissue. They affect the accuracy of needle placement, which in turn affects the effectiveness of needle-based therapies and biopsies. METHODS: In this study, a needle is inserted using a robot with two degrees of freedom. The needle is modelled as a flexible beam with clamped support at one end, and its deflection is estimated using online force/moment measurements at the needle base. To compensate for the needle deflection, the needle is axially rotated through 180 degrees . The needle deflection estimation data is used to find the insertion depths at which needle rotations are to be performed. RESULTS: A bevelled-tip needle was inserted into animal tissue. The needle deflection at the target was reduced by about 90%. It was observed that minimization of needle deflection reduced tissue deformation. The proposed method reduced needle deflection more than when needle insertion was performed with constant rotation. CONCLUSIONS: Estimating needle tip position using online force/moment measurement improves the accuracy of robot-assisted percutaneous procedures when imaging feedback is not available.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it