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Record W1965618263 · doi:10.1109/ultsym.2013.0197

Fabrication and performance of a miniaturized 64-element high-frequency endoscopic phased array

2013· article· en· W1965618263 on OpenAlexaff
Andre Bezanson, Robert B. A. Adamson, Jeremy A. Brown

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPhased arrayMaterials scienceBandwidth (computing)Computer scienceTelecommunications

Abstract

fetched live from OpenAlex

We have developed a 42 MHz, 64-element phased array transducer packaged in a 2.5 mm by 3.1 mm endoscopic form factor. The array is a forward looking semi-kerfed design based on a 0.68Pb(Mg1/3Nb2/3)O3-0.32PbTiO3(PMN-32%PT) single-crystal wafer with an element-to-element pitch of 38 microns. In order to achieve a miniaturized form factor, a novel technique of wire bonding the array elements to a polyimide flexible circuit board oriented parallel to the forward looking ultrasound beam and perpendicular to the array was developed. A technique of dicing partially into the back of the array was also implemented in order to improve the directivity of the array elements. The array was fabricated with a single layer P(VDF-TrFE)-copolymer matching layer and a polymethylpentene (TPX) lens for passive elevation focusing to a depth of 7 mm. The two-way -6 dB pulse bandwidth was measured to be 55% and the average electromechanical coupling (kT) for the individual elements was measured to be 0.62. The one-way -3 dB directivity from several array elements was measured and found to be ± 20 degrees, which was shown to be an improvement over an identical kerfless array. The -3 dB one-way elevation focus resulting from the TPX lens was measured to be 152 microns at the focal depth, and the focused lateral resolution was measured to be 80 microns at a steering angle of 0°. To generate beam profiles and images the probe was connected to a Visualsonics Vevo 2100 imaging platform which was reprogrammed to allow for phased array transmit beamforming and receive data collection. The collected RF data was then processed offline using a Matlab script to generate sector images. Focused one-way transmit radiation patterns were collected with a needle hydrophone. Two-way images were generated with a dynamic range of 60 dB for wire phantoms in water and a tissue-equivalent medium. Finally, ex-vivo tissue images were generated of porcine brain tissue.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.192
Teacher spread0.186 · 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 source (direct Gemma or distilled Codex), 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

Citations11
Published2013
Admission routes1
Has abstractyes

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