Robotic Needle Steering for Percutaneous Interventions: Sensing, Modeling, and Control
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Robotic needle steering plays a critical role in improving the precision and safety of percutaneous interventions across various clinical applications. However, manual needle steering remains challenged by operator‐dependent variability, physiological tremor, and limited adaptability to dynamic tissue deformation. To address these limitations, this review examines recent advances in robotic needle steering, structured around three core components: 1) sensing for closed‐loop needle steering, 2) modeling of soft tissue deformation and needle deflection, and 3) trajectory planning and closed‐loop control strategies. Furthermore, emerging trends are discussed in artificial intelligence‐driven autonomy and advanced biocompatible materials, highlighting their potential to enhance steering accuracy and real‐time adaptability in future robot‐assisted percutaneous procedures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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