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Record W2769518764 · doi:10.1109/ultsym.2017.8092453

An improved spread-spectrum method for high-frame-rate color Doppler ultrasound imaging

2017· article· en· W2769518764 on OpenAlexaff
Omar Mansour, Tamie L. Poepping, James C. Lacefield

Bibliographic record

Venue2017 IEEE International Ultrasonics Symposium (IUS) · 2017
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsWestern University
Fundersnot available
KeywordsClutterDoppler effectFrame rateComputer scienceAzimuthOpticsPhysicsAcousticsComputer visionRadarTelecommunications

Abstract

fetched live from OpenAlex

Ultrasound plane-wave imaging is desirable for its ability to achieve high frame rates, allowing the capture of fast dynamic events and continuous Doppler data. In most implementations, multiple low-resolution images from different plane-wave azimuthal steering angles are compounded to form a single high-resolution image, thereby reducing the effective frame rate and attenuating signals with high Doppler shifts. We recently introduced a spread-spectrum color Doppler imaging method [1] that produces high-resolution images without the use of compounding, thereby eliminating the trade-off between beam quality, frame rate, and the unaliased Doppler frequency limit. The method uses a Doppler ensemble formed from a long random sequence of transmit angles that randomizes the phase difference between echoes from the focal point and the out-of-cell (clutter) echoes, thereby spreading the clutter power in the Doppler frequency domain. The original spread-spectrum method suppressed vessel wall echoes, but did not address tissue clutter.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
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 score0.634
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.015
GPT teacher head0.325
Teacher spread0.309 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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