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Record W3195632328 · doi:10.1364/boe.428101

All-fiber few-mode optical coherence tomography using a modally-specific photonic lantern

2021· article· en· W3195632328 on OpenAlex
Martin Poinsinet de Sivry-Houle, Simon Beaudoin, Simon Brais-Brunet, Mathieu Dehaes, Nicolas Godbout, Caroline Boudoux

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

VenueBiomedical Optics Express · 2021
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsUniversité de MontréalUniversité de SherbrookePolytechnique Montréal
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of Canada
KeywordsOptical coherence tomographyOpticsInterferometryOptical fiberPhotonicsPhysics

Abstract

fetched live from OpenAlex

Optical coherence tomography (OCT) was recently performed using a few-mode (FM) fiber to increase contrast or improve resolution using a sequential time-domain demultiplexing scheme isolating the different interferometric signals of the mode-coupled backscattered light. Here, we present an all-fiber FM-OCT system based on a parallel modal demultiplexing scheme exploiting a novel modally-specific photonic lantern (MSPL). The MSPL allows for maximal fringe visibility for each fiber propagation mode in an all-fiber assembly which provides the robustness required for clinical applications. The custom-built MSPL was designed for OCT at 930 nm and is wavelength-independent over the broad OCT spectrum. We further present a comprehensive coupling model for the interpretation of FM-OCT images using the first two propagation modes of a few-mode fiber, validate its predictions, and demonstrate the technique using in vitro microbead phantoms and ex vivo biological samples.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.269
Teacher spread0.244 · 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