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Record W2098110745 · doi:10.1109/tmech.2008.924122

Robotic System for Closed-Bore MRI-Guided Prostatic Interventions

2008· article· en· W2098110745 on OpenAlexaff
A.A. Goldenberg, John Trachtenberg, Walter Kucharczyk, Yang Yi, Masoom A. Haider, Leo Ma, Robert Weersink, Cyrus Raoufi

Bibliographic record

VenueIEEE/ASME Transactions on Mechatronics · 2008
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMagnetic resonance imagingUltrasonic motorRobotAblationInterventional magnetic resonance imagingUltrasonic sensorComputer scienceIsocenterVisualizationActuatorBiomedical engineeringLaser ablationUltrasoundComputer visionArtificial intelligenceMedicineRadiologyLaserEngineeringPhysicsElectrical engineeringPiezoelectricityRadiation therapyOptics

Abstract

fetched live from OpenAlex

This paper reports on the development of a new closed-bore magnetic resonance imaging (MRI) compatible robotic system for image-guided prostatic interventions: ablation, brachytherapy, and biopsy. The first stage of development addresses only laser-based ablation. The robot actuators are ultrasonic motors. The first physical robot prototype was manufactured and tested in the MRI with an ablation tool. The tests covered magnetic resonance (MR) compatibility, tool visualization, and robot control accuracy. Robot tip position error is less than 2 mm at points closer than 0.5 m to the isocenter. A method to control ultrasonic motors for MRI-compatibility is reported.

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)0.001
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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.065
GPT teacher head0.349
Teacher spread0.284 · 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

Citations69
Published2008
Admission routes1
Has abstractyes

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