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Record W2081255842 · doi:10.1364/ol.33.000732

Artifact removal in Fourier-domain optical coherence tomography with a piezoelectric fiber stretcher

2008· article· en· W2081255842 on OpenAlex
Sébastien Vergnole, Guy Lamouche, M. Dufour

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueOptics Letters · 2008
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsNational Research Council Canada
FundersNational Research Council Canada
KeywordsOptical coherence tomographyOpticsArtifact (error)Fourier transformCoherence (philosophical gambling strategy)Phase modulationFrequency domainOptical fiberTransverse planeMaterials scienceComputer sciencePhysicsComputer visionPhase noise

Abstract

fetched live from OpenAlex

We describe an artifact removal setup swept-source optical coherence tomography (OCT) system that enables high-speed full-range imaging. We implement a piezoelectric fiber stretcher to generate a periodic phase shift between successive A-scans, thus introducing a transverse modulation. The depth ambiguity is then resolved by performing a Fourier filtering in the transverse direction before processing the data in the axial direction. The dc artifact is also removed. The key factor is that the piezoelectric fiber stretcher can be used to generate discrete phase shifts with a high repetition rate. The proposed experimental setup is a much improved version of the previously reported B-M mode scanning for spectral-domain OCT in that it does not generate additional artifacts. It is a simple and low-cost solution for artifact removal that can easily be applied.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
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
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
Teacher spread0.189 · 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