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Record W4408505294 · doi:10.1364/ol.557992

Effective interscan time for enhanced <i>in vivo</i> choriocapillaris imaging with OCT angiography

2025· article· en· W4408505294 on OpenAlexfundno aff
Mohammad Shahidul Islam, Jun Song, Ansel Chen, Zaid Mammo, Myeong Jin Ju

Bibliographic record

VenueOptics Letters · 2025
Typearticle
Languageen
FieldMedicine
TopicRenal and Vascular Pathologies
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaAlzheimer Society Research ProgramCanadian Cancer Society
KeywordsOpticsAngiographyMedicinePreclinical imagingIn vivoRadiologyPhysics

Abstract

fetched live from OpenAlex

imaging of the choriocapillaris (CC) remains challenging due to its dense microvascular structure and low reflectivity. While previous studies have explored various scanning protocols to enhance CC visualization, most approaches rely on oversampling, beam size adjustments, large numbers of repetitive B-scans (BM), and volume registration. However, interscan time-a critical parameter that influences flow contrast and vascular detail-has been largely overlooked. In this Letter, we introduce interscan time as a novel, to the best of our knowledge, CC imaging parameter and propose an optimized OCTA protocol by leveraging a 1.6 MHz FDML swept-source laser and step-bidirectional scanning method to investigate its impact across beam sizes and BM-scans. Our findings reveal that shorter interscan time significantly improves CC visualization by enhancing vessel contrast and preserving microvascular details, enabling better clinical assessment of retinal diseases such as age-related macular degeneration and diabetic retinopathy.

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 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 score0.051
Threshold uncertainty score0.450

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)0.0000.000

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 head0.003
GPT teacher head0.229
Teacher spread0.226 · 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.

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
Published2025
Admission routes1
Has abstractyes

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