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Record W1984405652 · doi:10.1109/tbme.2004.843295

Three-Dimensional Trajectory Assessment of an IVUS Transducer From Single-Plane Cineangiograms: A Phantom Study

2005· article· en· W1984405652 on OpenAlexafffund
Denis Sherknies, Jean Meunier, Rosaire Mongrain, Jean‐Claude Tardif

Bibliographic record

VenueIEEE Transactions on Biomedical Engineering · 2005
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsMontreal Heart InstituteUniversité de Montréal
FundersInstitut de Cardiologie de Montréal
KeywordsTransducerImaging phantomProjection (relational algebra)Iterative reconstructionTrajectoryPlane (geometry)CurvatureComputer visionAcousticsComputer scienceMathematicsGeometryOpticsPhysicsAlgorithm

Abstract

fetched live from OpenAlex

The recovery of the three-dimensional (3-D) path of the transducer used during an intravascular ultrasound (IVUS) examination is of primary importance to assess the exact 3-D shape of the vessel under study. Traditionally, the reconstruction is done by simply stacking the images during the pullback, or more recently using biplane angiography to recover the vessel curvature. In this paper, we explain, how single-plane angiography can be used with two projection models, to perform this task. Two types of projection geometry are analyzed: weak-perspective and full-perspective. In weak-perspective projection geometry, the catheter path can be reconstructed without prior transducer depth information. With full-perspective projection geometry, precise depth location of reference points are needed in order to minimize the error of the recovered transducer angle of incidence. The transducer angulation reconstruction is based on the foreshortening effect as seen from the X-ray images. By comparing the measured to the true transducer length, we are able to get its incidence angle. The transducer trajectory is reconstructed by stitching together the different estimated angulations obtained from each image in a cineangiogram sequence. The method is described and validated on two helical vessel phantoms, giving on average a reconstructed path that is less than 2 mm distant from the true path when using full-perspective projection.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
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)0.0010.000

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 head0.021
GPT teacher head0.285
Teacher spread0.264 · 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.

Study designSimulation or modeling
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

Citations8
Published2005
Admission routes2
Has abstractyes

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