MétaCan
Menu
Back to cohort
Record W4249618906 · doi:10.1364/ecbo.2009.7369_1n

Angular domain optical imaging of turbid media using enhanced micro-tunnel filter arrays

2009· article· en· W4249618906 on OpenAlexaff
Fartash Vasefi, Benny Hung, Bożena Kamińska, Glenn H. Chapman, Jeffrey J. L. Carson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsWestern UniversitySimon Fraser UniversityLawson Health Research Institute
Fundersnot available
KeywordsOpticsCollimated lightPhotonTotal internal reflectionPhysicsAngular resolution (graph drawing)ScatteringFilter (signal processing)Optical filterMaterials scienceLaser

Abstract

fetched live from OpenAlex

We experimentally characterized the angular distribution and proportion of minimally deviated quasi-ballistic (snake) photons versus multiply scattered photons in a homogenous turbid medium. The study examined the angular distribution of photons propagating through and exiting the highly scattering medium over a narrow range about the axis of a collimated light source in trans-illumination mode. The measurements were made using an angular domain imaging system that employed one of five silicon micro-machined arrays of micro-tunnels each with a range of different acceptance angles and micro-tunnel structures. The balance between quasi-ballistic photons and unwanted multiply scattered photons accepted by the micro-machined angular filters was measured in order to determine the optimum range of acceptance angles for the system. The experiments were performed in tissue mimicking phantoms using a 2-cm thick optical cell with 0.25% Intralipid™ and a near infrared laser. This paper also presents experimental results of the angular domain imaging system employing novel micro-tunnel arrays with minimal internal reflection which can accept the non-scattered light exiting from the turbid medium within its small acceptance angle more efficiently. Our experiments reveal that image contrast was improved from 20% to 30% by employing an angular filter array with minimal internal reflection compared to conventional square-shaped filter arrays of identical size.

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 score0.162
Threshold uncertainty score0.614

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicOptical Coherence Tomography ApplicationsFrench-language works237,207