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Record W1991260960 · doi:10.4236/jbise.2011.412093

Imaging of arterial plaque by quadrature swept-source optical coherence tomography with signal to noise ratio enhancements

2011· article· en· W1991260960 on OpenAlexafffund
Youxin Mao, Costel Flueraru, Shoude Chang

Bibliographic record

VenueJournal of Biomedical Science and Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsNational Research Council CanadaInstitute for Microstructural Sciences
FundersNational Research Council Canada
KeywordsOptical coherence tomographyInterferometryOpticsMaterials scienceBiomedical engineeringSIGNAL (programming language)Penetration depthTomographyPhysicsMedicineComputer science

Abstract

fetched live from OpenAlex

Arterial plaque from a myocardial infarction-prone Watanabe heritable hyperlipidemic (WHHLMI) rabbit is visualized and characterized using a signal to noise ratio enhanced swept-source optical coherence tomography system with a quadrature interferometer (QSS-OCT). A semiconductor optical amplifier is used in the sample arm to amplify the weak signal scattered from arterial plague. Signal to noise ratio improvement are demonstrated in our QSS-OCT system. This finding results into an increase of the penetration depth possible in OCT images, from 1 mm to 2 mm. Preliminary results show that vulnerable plaque with fibrous cap, macrophage accumulations and calcification in the arterial tissue are measurable with our QSS-OCT system.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 studies0.0000.000
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 head0.005
GPT teacher head0.197
Teacher spread0.192 · 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

Citations1
Published2011
Admission routes2
Has abstractyes

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