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Record W2169748775 · doi:10.1109/tro.2008.2001353

Autonomous Image-Guided Robot-Assisted Active Catheter Insertion

2008· article· en· W2169748775 on OpenAlex

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.

Bibliographic record

VenueIEEE Transactions on Robotics · 2008
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsCatheterFluoroscopyActuatorRobotArtificial intelligenceComputer scienceComputer visionBiomedical engineeringSurgerySimulationMedicine

Abstract

fetched live from OpenAlex

Interventional cardiologists are at great risk from radiation exposure due to lengthy procedures performed under X-ray radiations. Angioplasty is one such procedure wherein the clinician guides a catheter into the femoral artery under X-rays and the procedure often extends to over 50 min. A clinician performs several hundred such procedures over his/her lifetime, leading to an accumulation of the total radiation he/she is exposed to. In this paper, we investigate autonomous robot-assisted insertion of an active catheter instrumented with shape memory alloy (SMA) actuators using image guidance. The tip of the active catheter is tracked in real time to provide information on the location of the catheter that determines the optimal stroke length of insertion for the robot and the necessary bending angle for the active catheter. The catheter is autonomously guided from the point of entry to the site of plaque buildup, thereby shielding the clinician from harmful radiation due to the X-rays used for imaging and providing a more ergonomic approach for catheter insertion. Experimental results are given to illustrate the robot-assisted catheter insertion procedure using image guidance.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score1.000

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 head0.030
GPT teacher head0.242
Teacher spread0.212 · 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