MétaCan
Menu
Back to cohort
Record W4237014366 · doi:10.1109/iembs.2006.4397508

High-Precision Absolute Positioning of Medical Instruments in MRI Systems

2006· article· en· W4237014366 on OpenAlexaff
Eric Aboussouan, Sylvain Martel

Bibliographic record

VenueConference proceedings · 2006
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversité de MontréalPolytechnique Montréal
Fundersnot available
KeywordsPosition (finance)Magnetic resonance imagingConvolution (computer science)Distortion (music)Real-time MRIComputer scienceComputer visionArtificial intelligenceMedicineRadiologyArtificial neural network

Abstract

fetched live from OpenAlex

An absolute positioning technique has been developed for ferromagnetic markers in medical instruments and untethered devices operating in a magnetic resonance imaging (MRI) system. This technique allows high precision 3D readings of the location of the device with respect to the absolute center of the MRI bore. The local magnetic field induced by the device is used as a signature for localization from 3 one-dimensional projections. A convolution between two acquisitions based on opposite read-out gradients is used to obtain the absolute position of the device without any effect from the susceptibility distortion. The validity of the method has been demonstrated and its precision was found sufficient to correctly register the device position with MRI images

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)0.002
metaresearch head score (Gemma)0.005
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 score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.017
GPT teacher head0.302
Teacher spread0.285 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueConference proceedingsSame topicAdvanced MRI Techniques and ApplicationsFrench-language works237,207