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Record W4402166220 · doi:10.32920/26866519

The CathEye: A Forward-Looking Ultrasound Catheter for Image-Guided Cardiovascular Procedures

2024· preprint· en· W4402166220 on OpenAlexaff
Alykhan Sewani

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsToronto Metropolitan UniversityUniversity of Waterloo
Fundersnot available
KeywordsCatheterUltrasoundMedical physicsComputer scienceComputer visionImage (mathematics)RadiologyMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

Catheter-based procedures suffer from a lack of visualization due to the use of 2-D X-ray to guide 3-D operations and the lack of soft tissue contrast, which leaves the surgeon blind to the morphology of the anatomy. We propose using the CathEye, a high-precision steerable catheter with an integrated 40MHz ultrasound transducer, to create wide FOV, 3-D images of the surgical workspace. The CathEye uses an expandable cable-driven parallel mechanism to provide localized control and tracking of the distal tip of the catheter relative to the anatomy. Ultrasound signals are acquired simultaneously with position data to generate a 3-D surface reconstruction. The imaging capabilities of the CathEye were evaluated by confining the device to various tortuous paths and scanning a tissue-mimicking phantom and an ex vivo lesion. The CathEye can track an interventional tool overtop the generated image, allowing for an interventional device fully integrated with 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.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.299
Teacher spread0.282 · 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
GenreMethods

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

Citations0
Published2024
Admission routes1
Has abstractyes

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