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Record W2108683889 · doi:10.1109/58.883525

A history of medical and biological imaging with polyvinylidene fluoride (PVDF) transducers

2000· article· en· W2108683889 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · 2000
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsPrincess Margaret Cancer CentreHealth Sciences CentreOntario Institute for Cancer ResearchUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsPolyvinylidene fluorideTransducerMaterials scienceCeramicMedical imagingAcousticsNondestructive testingAcoustic impedanceUltrasonic sensorUltrasoundFerroelectricityBiomedical engineeringPolymerComposite materialOptoelectronicsRadiologyEngineeringDielectricMedicine

Abstract

fetched live from OpenAlex

Polyvinylidene fluoride (PVDF) is a ferroelectric polymer with unique properties suitable for use in a wide range of medical and biological imaging applications. Most notable among these is its low acoustic impedance, which matches that of the body reasonably well, and its flexible mechanical properties. This paper traces the exploitation of PVDF as a transducer material from its early beginnings for thyroid and breast imaging to its current well-established applications in ultrasound biomicroscopy. Although PVDF's electromechanical properties fall short of composite ceramic materials in the traditional diagnostic frequency range, it has significant advantages in the 25-to 100-MHz range. Design criteria for high frequency transducers are reviewed, and examples of relevant medical and biological images are used to illustrate the excellent image quality obtained with this remarkable material.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.834
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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