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Record W2124118366 · doi:10.1109/tmi.2008.2011899

A 3-D High-Frequency Array Based 16 Channel Photoacoustic Microscopy System for <emphasis emphasistype="italic">In Vivo</emphasis> Micro-Vascular Imaging

2009· article· en· W2124118366 on OpenAlexaff
Rachel R. Bitton, Roger J. Zemp, Jesse T. Yen, Lihong V. Wang, K. Kirk Shung

Bibliographic record

VenueIEEE Transactions on Medical Imaging · 2009
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsUniversity of Alberta
FundersNational Institute of Biomedical Imaging and Bioengineering
KeywordsEmphasis (telecommunications)Photoacoustic imaging in biomedicineMicroscopyChannel (broadcasting)OpticsBiomedical engineeringComputer scienceMaterials sciencePhysicsTelecommunicationsMedicine

Abstract

fetched live from OpenAlex

This paper discusses the design of a novel photoacoustic microscopy imaging system with promise for studying the structure of tissue microvasculature for applications in visualizing angiogenesis. A new 16 channel analog and digital high-frequency array based photoacoustic microscopy system (PAM) was developed using an Nd:YLF pumped tunable dye laser, a 30 MHz piezo composite linear array transducer, and a custom multichannel receiver electronics system. Using offline delay and sum beamforming and beamsteering, phantom images were obtained from a 6 mum carbon fiber in water at a depth of 8 mm. The measured -6 dB lateral and axial spatial resolution of the system was 100+/-5 microm and 45+/-5 microm, respectively. The dynamic focusing capability of the system was demonstrated by imaging a composite carbon fiber matrix through a 12.5 mm imaging depth. Next, 2-D in vivo images were formed of vessels around 100 mum in diameter in the human hand. Three-dimensional in vivo images were also formed of micro-vessels 3 mm below the surface of the skin in two Sprague Dawley rats.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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.

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

Citations28
Published2009
Admission routes1
Has abstractyes

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