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Record W2007559104 · doi:10.1117/1.jbo.18.9.090502

Optical resolution photoacoustic microendoscopy with ultrasound-guided insertion and array system detection

2013· article· en· W2007559104 on OpenAlexafffund
Parsin Haji Reza, Tyler Harrison, Alexander Forbrich, Roger J. Zemp

Bibliographic record

VenueJournal of Biomedical Optics · 2013
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta InnovatesKillam TrustsUniversity of AlbertaCancer Research Institute
KeywordsMaterials scienceOpticsBundleGalvanometerOptical fiberTransducerFiber bundleLaserPhotoacoustic effectPhysicsAcoustics

Abstract

fetched live from OpenAlex

Using a 0.8-mm-diameter image guide fiber bundle consisting of 30,000 single-mode fibers and an external linear array transducer, we demonstrate a dual-mode photoacoustic system capable of ultrasound-guided microendoscope insertion and photoacoustic imaging. The array optical resolution photoacoustic microendoscopy (AOR-PAME) system is designed to visualize the placement of the distal end of an endoscopy probe several centimeters into tissue, transmit scanning focused laser pulses into tissues via the fiber bundle, and acquire the generated photoacoustic signals. A ytterbium-doped fiber laser is tightly focused and is scanned across the proximal tip of the image guide fiber bundle using a two-dimensional galvanometer scanning mirror system. The end of the fiber bundle is used in contact mode with the object. The capabilities of AOR-PAME are demonstrated by imaging carbon fiber networks embedded in tissue-mimicking phantoms and the ears of a 60-g rat. The lateral resolution and signal-to-noise ratio are measured as 9 μm and 40 dB, respectively.

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 score0.636
Threshold uncertainty score0.512

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 head0.005
GPT teacher head0.186
Teacher spread0.182 · 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

Citations9
Published2013
Admission routes2
Has abstractyes

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