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Record W2107801697 · doi:10.1109/robot.2009.5152567

Real-time positioning and tracking technique for endovascular untethered microrobots propelled by MRI gradients

2009· article· en· W2107801697 on OpenAlexaff
Ouajdi Felfoul, Eric Aboussouan, Arnaud Chanu, Sylvain Martel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMicro and Nano Robotics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTracking (education)Computer visionMagnetic resonance imagingComputer scienceArtificial intelligenceRobotReal-time MRIPositioning systemTracking systemAcousticsPhysicsKalman filterRadiology

Abstract

fetched live from OpenAlex

A real-time positioning and tracking technique for untethered devices or robots magnetically propelled by a clinical magnetic resonance imaging (MRI) system is described. The local magnetic field induced by the device, composed of a ferromagnetic material, is used as a signature to localize the device on three one-dimensional projections. A high-precision 3D circular-motion system was used to assess the precision and accuracy of this method. The integration of this technique inside propulsion and imaging MRI sequences was also achieved to demonstrate the feasibility of this tracking scheme in a closed-loop control scheme. Finally, in vivo tracking during automatic navigation of an untethered device in the carotid artery of a living animal is demonstrated.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.758
Threshold uncertainty score0.530

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.229
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2009
Admission routes1
Has abstractyes

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