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Record W2126727782 · doi:10.1143/jjap.39.3220

Simulation of Ultrasonic Displacement in Random Medium Using Ultrasonic Speckle Tracking

2000· article· en· W2126727782 on OpenAlexaff
Tjundewo Lawu, Mitsuhiro Ueda

Bibliographic record

VenueJapanese Journal of Applied Physics · 2000
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsSpeckle patternUltrasonic sensorImpulse (physics)Artifact (error)Impulse responseAcousticsDisplacement (psychology)OpticsTracking (education)SIGNAL (programming language)Materials sciencePhysicsComputer scienceComputer visionMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

The quantitative evaluation of ultrasonic displacement in tissue under externally applied forces is a necessary step in the field of ultrasonic diagnostics. In this study, the speckle tracking method is used to investigate motion artifact produced by a rotating tissue. An analytic prediction of this motion artifact in relation to system characteristics (i.e., beam width, pulse duration, frequency and phase of the signal) is presented. The tissue is modeled as a random array of numerous point scatterers, and RF signals are computed based on the convolutions between the transmission pulse and the impulse response of each scanning line. The preliminary results show that the artifact resulting from the speckle tracking method depends on the beam width. The method is quite general and can be extended to study the effects of other tissue motion, in particular, the deformation of 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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.554

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 studies0.0000.000
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 head0.015
GPT teacher head0.276
Teacher spread0.260 · 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 designSimulation or modeling
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

Citations4
Published2000
Admission routes1
Has abstractyes

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