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Record W2039078214 · doi:10.1002/mrm.10325

Remote control of catheter tip deflection: An opportunity for interventional MRI

2002· article· en· W2039078214 on OpenAlexaff
Timothy P. L. Roberts, W.V. Hassenzahl, Steven W. Hetts, Ronald L. Arenson

Bibliographic record

VenueMagnetic Resonance in Medicine · 2002
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImaging phantomScannerCatheterElectromagnetic coilDeflection (physics)Magnetic fieldBiomedical engineeringComputer sciencePhysicsRadiologyMedicineElectrical engineeringEngineeringOpticsArtificial intelligence

Abstract

fetched live from OpenAlex

This study seeks to exploit the high magnetic field environment of a clinical MRI scanner and demonstrate the technical feasibility of developing a catheter whose tip can be remotely oriented within the magnetic field by applying a DC current to a coil wound around the catheter tip to generate a magnetic moment and consequent deflection. To achieve arbitrary three-dimensional deflections, a three-axis coil was wound on a 1.5 Fr cylindrical catheter. By applying DC currents in the 100 mA range, this catheter was successfully guided through a 3D phantom maze, mimicking the vasculature, under MR imaging guidance. Feasibility was demonstrated that the strong ambient magnetic field of the MR scanner offers a special opportunity to develop simple devices that can be remotely steered to sites of clinical interest.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.067
GPT teacher head0.363
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), 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

Citations91
Published2002
Admission routes1
Has abstractyes

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