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Record W2053352255 · doi:10.1364/ao.48.006448

Transmission and fluorescence angular domain optical projection tomography of turbid media

2009· article· en· W2053352255 on OpenAlexaff
Fartash Vasefi, Eldon Ng, Bożena Kamińska, Glenn H. Chapman, Kevin Jordan, Jeffery J. L. Carson

Bibliographic record

VenueApplied Optics · 2009
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsWestern UniversityLawson Health Research InstituteSimon Fraser University
Fundersnot available
KeywordsOpticsCollimated lightCollimatorPhysicsAngular resolution (graph drawing)Projection (relational algebra)PhotonComputer science

Abstract

fetched live from OpenAlex

When imaging through turbid media, objects are often blurred by scattered light. An optical collimator (i.e., an angular filter array) improves images by accepting only photons propagating within a narrow solid angle about the direction of the incident light. These photons are expected to participate in a limited number of small-angle scattering events, maintaining their original propagation direction and, finally, contributing to the development of a faithful image of an object within a turbid medium. The collimation method, also referred to as angular domain imaging (ADI), applies to a see-through configuration where the incident collimated light beam can be aligned with the collimator in a transillumination mode of operation. In this paper, we present angular domain optical projection tomography (ADOPT), a method that can extract depth information of optical contrast in turbid media with high longitudinal resolution based on ADI technology. The resolution of the ADI system has been tested over various depths in a 5 cm optical cuvette using a resolution target suspended in a homogeneous turbid medium. The ADOPT system reconstructed images from a series of angular domain projections collected at angular intervals. The system was used to measure the attenuation of an absorbing target in transmission mode (t-ADOPT) and to measure the light emitting from a fluorescent target (f-ADOPT). Tissue-mimicking phantoms were used to validate the performance of the method. In the t-ADOPT configuration, a background scattered light estimation and subtraction methodology was introduced to improve the imaging contrast. A target consisting of two graphite rods (0.9 mm diameter) was suspended in the cuvette by a rotation stage. An Indocyanine Green-filled glass rod was used as an imaging target in the f-ADOPT arrangement. The target was placed in a manner such that the line of laser light was perpendicular to the longitudinal axis of the rods. Several projections were collected at increments of 1.8 degrees and compiled into a sinogram. A transverse image was reconstructed from the sinogram by using filtered backprojection and image contrast was improved by experimental scatter measurements using a wedge prism and an image processing algorithm. The submillimeter target embedded in a 2 cm thick scattering medium (reduced scattering coefficient < or = 2.4 cm(-1)) was discernable in both the sinograms and the reconstructed images. In the f-ADOPT system, fluorescent line targets <1 cm in diameter embedded in a 2 cm thick scattering medium (reduced scattering coefficient < or = 0.8 cm(-1)) were discernable in both the sinograms and the reconstructed images. The proposed method could be used as the basis to construct an optical tomographic scanner for simultaneous absorption and fluorescence-based imaging of biological specimens (i.e., up to 7 mm across).

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 score0.247
Threshold uncertainty score0.424

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 head0.007
GPT teacher head0.260
Teacher spread0.253 · 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

Citations13
Published2009
Admission routes1
Has abstractyes

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