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Ablation Catheter Tracking with Ultrawideband Radar

2023· article· en· W4381745254 on OpenAlexaff
Seyedali Mohammadi, M. Ali Tavallaei, Raviraj Adve

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsComputer visionArtificial intelligenceComputer scienceTracking (education)RadarCatheterRadar trackerRadar engineering detailsPosition (finance)Radar imagingTracking systemObject detectionKalman filterMedicineRadiologySegmentationTelecommunications

Abstract

fetched live from OpenAlex

Minimally invasive surgeries result in less trauma, less bleeding and faster recovery compared to traditional open surgeries. Optical tracking systems are used to detect and localize surgical tools during the procedure. Complications arise when there are adverse lighting conditions, or the tools are occluded by tissue, smoke, or blood spatters. To address this issue, a radar-based tracking solution was proposed motivated by its ability to detect objects through occlusions. In this paper, the efficacy of ultrawideband radar for tracking of an ablation catheter was investigated. Three experiments were conducted to test the localization and position tracking of the catheter tip and the detection of catheter pose. Results from the experiment show that a single sensor could localize and track the position of the catheter with 1cm of spatial accuracy, and an array of sensors could be implemented for pose detection. We also discuss the existing limitations of the proposed radar-based procedure.

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 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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.240

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 head0.010
GPT teacher head0.200
Teacher spread0.190 · 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 teacher head, 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

Citations0
Published2023
Admission routes1
Has abstractyes

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