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Record W4224064770 · doi:10.1117/12.2609021

In-vivo non-contact functional and structural ophthalmic imaging using a dual-modal photoacoustic remote sensing and swept-source optical coherence tomography system

2022· article· en· W4224064770 on OpenAlexaff
Nima Abbasi Firoozjah, Zohreh Hosseinaee, Nicholas Pellegrino, Layla Khalili, Lyazzat Mukhangaliyeva, Parsin Haji Reza

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOptical coherence tomographyPhotoacoustic imaging in biomedicineMaterials scienceOpticsPhotoacoustic tomographyTomographyPhotoacoustic Doppler effectBiomedical engineeringAbsorption (acoustics)PhysicsMedicine

Abstract

fetched live from OpenAlex

In this work, a synchronized dual-modal imaging system is used for in-vivo, non-contact ophthalmic imaging. The apparatus is comprised of both Photoacoustic Remote Sensing (PARS) and Swept-Source Optical Coherence Tomography (SS-OCT) subsystems. The PARS utilizes a multi-wavelength excitation source to target hemoglobin absorption and an 830 nm interrogation source to detect photoacoustic signals. PARS provides the measurements for computing blood oxygen saturation (sO2) mapping in the mouse and rat eyes. Meanwhile, a 1060 nm SS-OCT is employed to obtain volumetric tissue structure. To our knowledge, this is the first report of non-contact functional photoacoustic imaging in ophthalmic applications.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 communication0.0000.001
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 head0.007
GPT teacher head0.203
Teacher spread0.196 · 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
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
Published2022
Admission routes1
Has abstractyes

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