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Record W2054279113 · doi:10.1109/bmei.2013.6746969

Compatibility of US motors for development of MRI-guided surgical robot

2013· article· en· W2054279113 on OpenAlex
Wendong Wang, Yikai Shi, Xiaoqing Yuan, A.A. Goldenberg, Peyman Shokrollahi

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsUniversity of Toronto
FundersHospital for Sick Children
KeywordsScannerIsocenterCompatibility (geochemistry)RobotActuatorPerpendicularComputer scienceBiomedical engineeringMaterials scienceArtificial intelligencePhysicsEngineeringOpticsImaging phantomMathematics

Abstract

fetched live from OpenAlex

US (Ultrasonic) motors have potential applications as MR-compatible actuators for MRI-guided surgical robots. MR compatibility test of US motors (Shinsei USR 30 and USR 60) were performed in 3T MRI scanner under baseline, power-off, power-on, and moving configurations with mounting orientations parallel and perpendicular to the longitudinal bore axis. Normalized SNR was used to calculate the MR compatibility of US motors. The results show that the safe distances for USR 30 and USR 60 from the isocenter are 15cm and 20cm, respectively. Moving configuration decreased the normalized SNR by 15%-25%. In the same mounting orientation, three imaging sequences performed differently in terms of quality of MR images. To conclude, the Shinsei USR 30 and USR 60 are suitable for providing actuation of MRI-guided surgical robot during real-time imaging, and the MR compatibility could be improved by selecting suitable safe distance and mounting orientation.

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.283
Threshold uncertainty score0.179

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 head0.033
GPT teacher head0.266
Teacher spread0.233 · 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

Quick stats

Citations7
Published2013
Admission routes2
Has abstractyes

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