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Record W1977983707 · doi:10.1117/1.3505020

Angular domain transillumination imaging optimization with an ultrafast gated camera

2010· article· en· W1977983707 on OpenAlexafffund
Fartash Vasefi, Mohamadreza Najiminaini, Eldon Ng, Bożena Kamińska, Glenn H. Chapman, Jeffery J. L. Carson

Bibliographic record

VenueJournal of Biomedical Optics · 2010
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsWestern UniversitySimon Fraser UniversityLawson Health Research Institute
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTransilluminationPhotonOpticsPhysicsFilter (signal processing)Angular resolution (graph drawing)ScatteringAngular diameterComputer scienceComputer vision

Abstract

fetched live from OpenAlex

By employing high-aspect-ratio parallel microchannels as an angular filter, quasiballistic photons sensitive to internal structures in a turbid medium can be captured. Scattered photons exiting the turbid medium typically exhibit trajectories with random angles compared to the initial trajectory and are mostly rejected by the filter. However, angular filter arrays cannot differentiate between quasiballistic photons (early arriving) and photons that happen to attain a scattered trajectory that is within the acceptance angle (late arriving). Therefore, we have two objectives: (1) to experimentally characterize the angular distribution and proportion of minimally deviated quasiballistic photons and multiply scattered photons in a turbid medium and (2) to combine time and angular gating principles so that early and late arriving photons can be distinguished. From the angular distribution data, the angular filter with angular acceptance about 0.4 deg yields the highest image contrast for transillumination images. The use of angular domain imaging(ADI) with time-gating enables visualization of submillimeter absorbing objects with approximately seven times higher image contrast compared to ADI in a turbid medium with a scattering level of six times the reduced mean free path.

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)0.001
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 score0.611
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.004
GPT teacher head0.274
Teacher spread0.270 · 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

Citations12
Published2010
Admission routes2
Has abstractyes

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