MétaCan
Menu
Back to cohort
Record W2915959260 · doi:10.1117/12.2510296

Combined speckle variance optical coherence tomography and multiphoton microscopy for in vivo chick CAM imaging

2019· article· en· W2915959260 on OpenAlexaff
Yonghan Zhou, Shuo Tang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsOptical coherence tomographyBiomedical engineeringSpeckle patternBlood flowMaterials scienceMicroangiographyVisualizationMicrocirculationOptical tomographyMicroscopyTomographyComputer scienceOpticsArtificial intelligencePhysicsMedicine

Abstract

fetched live from OpenAlex

Combining optical coherence tomography (OCT) and multiphoton microscopy (MPM) can provide multimodal imaging of the microstructure of biological tissues. As a functional extension of conventional OCT, speckle variance OCT (SVOCT) can be applied to image microvasculature to improve the blood vessel visualization. In this paper, a combined SVOCT and MPM system is developed to visualize the chorioallantoic membrane (CAM) of a chick embryo, which contains extensive blood vessel network. Based on the different temporal decorrelation characteristics of the fluid flow and the surrounding stationary structure, SV-OCT enables enhanced contrast of fluid flow from the surrounding structure. As a result, SV-OCT can achieve detailed mapping of the CAM microvasculature at the tissue level. Meanwhile, MPM enables vascular imaging at the cellular level, where two-photon excitation fluorescence (TPEF) images fluorescein dye injected into the blood stream, and second harmonic generation (SHG) visualizes the collagen fiber structures in the vessel wall and the surrounding tissues. Therefore, the combined SV-OCT and MPM system provides complementary information about the microvasculature structures in the chick CAM. The combined system is shown to be a powerful tool for interpreting the microvasculature, by allowing the visualization of the blood vessel network in a relatively large field of view at the tissue level with SV-OCT, and by providing cellular-level information in local regions of interest with MPM.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.422
Threshold uncertainty score0.767

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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
Published2019
Admission routes1
Has abstractyes

Explore more

Same topicOptical Coherence Tomography ApplicationsFrench-language works237,207