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Record W2144362288 · doi:10.1109/biorob.2010.5626987

Preliminary evaluation of a MRI-compatible modular robotic system for MRI-guided prostate interventions

2010· article· en· W2144362288 on OpenAlexaff
Sang‐Eun Song, Nathan Cho, Junichi Tokuda, Nobuhiko Hata, Clare M. Tempany, Gábor Fichtinger, Iulian Iordachita

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsQueen's University
FundersNational Center for Research ResourcesNational Cancer Institute
KeywordsModular designImaging phantomMagnetic resonance imagingProstate cancerMedical physicsComputer scienceMedicineRadiologyCancer

Abstract

fetched live from OpenAlex

Magnetic Resonance Imaging (MRI) guided robotic interventions have been introduced in order to advance prostate cancer detection and treatment. To overcome problems of such robotic interventions, we have been developing a pneumatically actuated MRI-compatible modular robotic system for MRI-guided transperineal prostate intervention and its interventional procedure. For system evaluation, a series of experiments have been conducted and this paper reports a needle insertion experiment using prostate phantom and patient mockup trials. The needle insertion experiment resulted in noticeable consistent error in one direction, which we will investigate further. Nonetheless, patient mockup experiences suggest that the modular robotic system and its interventional procedure are well integrated and implemented in clinical environment.

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)0.004
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: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.048
GPT teacher head0.308
Teacher spread0.260 · 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

Citations17
Published2010
Admission routes1
Has abstractyes

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