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Record W2111741040 · doi:10.1109/58.883543

A 100-200 MHz ultrasound biomicroscope

2000· article· en· W2111741040 on OpenAlexaff
D.A. Knspik, B.G. Starkoski, Charles J. Pavlin, F. Stuart Foster

Bibliographic record

VenueIEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · 2000
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsHealth Sciences CentreOntario Institute for Cancer ResearchUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsUltrasoundTransducerFrame rateMaterials scienceAttenuationOpticsImage resolutionUltrasonic sensorBiomedical engineeringLithium niobateAcousticsPhysicsOptoelectronicsMedicine

Abstract

fetched live from OpenAlex

The development of higher frequency ultrasound imaging systems affords a unique opportunity to visualize living tissue at the microscopic level. This work was undertaken to assess the potential of ultrasound imaging in vivo using the 100-200 MHz range. Spherically focused lithium niobate transducers were fabricated. The properties of a 200 MHz center frequency device are described in detail. This transducer showed good sensitivity with an insertion loss of 18 dB at 200 MHz. Resolution of 14 /spl mu/m in the lateral direction and 12 /spl mu/m in the axial direction was achieved with f/1.14 focusing. A linear mechanical scan system and a scan converter were used to generate B-scan images at a frame rate up to 12 frames per second. System performance in B-mode imaging is limited by frequency dependent attenuation in tissues. An alternative technique, zone-focus image collection, was investigated to extend depth of field. Images of coronary arteries, the eye, and skin are presented along with some preliminary correlations with histology. These results demonstrate the feasibility of ultrasound biomicroscopy In the 100-200 MHz range. Further development of ultrasound backscatter imaging at frequencies up to and above 200 MHz will contribute valuable information about tissue microstructure.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.234
Teacher spread0.226 · 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

Citations68
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Ultrasonics Ferroelectrics and Frequency ControlSame topicUltrasound Imaging and ElastographyFrench-language works237,207