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Record W2054686771 · doi:10.1117/1.3470336

Combined photoacoustic and oblique-incidence diffuse reflectance system for quantitative photoacoustic imaging in turbid media

2010· article· en· W2054686771 on OpenAlexafffund
Janaka C. Ranasinghesagara, Roger J. Zemp

Bibliographic record

VenueJournal of Biomedical Optics · 2010
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaTerry Fox FoundationUniversity of AlbertaMinistry of Advanced Education, Government of Alberta
KeywordsOpticsMaterials sciencePhotoacoustic imaging in biomedicineAttenuation coefficientLaserImaging phantomAbsorption (acoustics)Photoacoustic Doppler effectPhotoacoustic effectFluenceDiffuse optical imagingTomographyPhysics

Abstract

fetched live from OpenAlex

While photoacoustic imaging is capable of producing high-resolution biomedical images with optical absorption contrast, optical property quantification has thus far remained challenging. One reason for this is that laser-induced photoacoustic signal amplitudes are proportional to not only the local optical absorption coefficient, but also the local laser fluence in the tissue. Unfortunately, local laser fluence is often unknown, but could possibly be estimated if local bulk tissue optical properties were known. One method to estimate tissue optical properties is a technique known as oblique incidence diffuse reflectance (OIR). We report on an integrated OIR and photoacoustic imaging system and demonstrate, using phantom experiments, improved ability to quantitatively estimate optical properties of a turbid medium.

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)0.002
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 score0.982
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.246
Teacher spread0.239 · 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

Citations18
Published2010
Admission routes2
Has abstractyes

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