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Record W1607008155

CODED EXCITATION METHODS FOR ULTRASOUND HARMONIC IMAGING

2007· article· en· W1607008155 on OpenAlexaffvenue
Roozbeh Arshadi, Alfred C. H. Yu, R.S.C. Cobbold

Bibliographic record

VenueCanadian acoustics · 2007
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChirpBandwidth (computing)AcousticsHarmonicWaveformSecond-harmonic imaging microscopyTransducerFrequency domainNonlinear systemHarmonic analysisFourier transformOpticsComputer scienceElectronic engineeringPhysicsRadarEngineeringTelecommunicationsSecond-harmonic generationComputer vision
DOInot available

Abstract

fetched live from OpenAlex

Coded excitation methods offer the potential for improving the SNR without increasing the peak transmitted power and without sacrificing resolution.Our study examines the potential application o f coded waveforms, specifically FM chirps, in harmonic imaging.Such a system, in which nonlinear echoes from tissue are used to form the image, requires the extraction and compression o f the second harmonic portion of the echo signal.Our objective is to obtain the second harmonic using just one transmission, thereby avoiding problems of frame rate reduction and movement artifacts associated with multiple transmission schemes.With the help o f an efficient method for predicting the transient nonlinear field from a focused transducer, design issues such as waveform and bandwidth selection, as well as filters for second harmonic extraction and compression are examined.Simulations reveal the presence of axial sidelobes in the compressed echo waveform as the bandwidth of the transmitted chirp is increased.These sidelobes, resulting from the overlap o f the fundamental and third harmonic bands with the second harmonic, cannot be removed using conventional Fourier filtering.Alternative filtering techniques which utilize the separation o f the harmonic bands o f a backscattered chirp in the joint time-frequency domain are suggested. s o m m a i r eLes méthodes d'excitation codée ont le potentiel d 'améliorer le ratio signal-bruit sans augmenter la puissance maximale transmise et sans sacrifier la résolution.Notre étude examine l'application potentielle de formes d'onde codées, plus spécifiquement de compression d 'impulsions FM pour imagerie harmonique.Dans un tel système, les échos non-linéaires provenant du tissu sont utilisés afin de former l'image, ce qui requiert l 'extraction et la compression de la deuxième portion harmonique du signal d'écho.Notre objectif est d 'obtenir le deuxième harmonique en utilisant seulement une transmission, évitant ainsi des problèmes de réduction du temps d 'image et d 'artefacts de mouvement associés avec de multiples schémas de transmission.En utilisant une méthode efficace de prédiction du champs nonlinéaire transitoire provenant d'un transducteur focalisé, des problèmes de conception tels que la sélection de forme d 'onde et de la largeur de bande, ainsi que de filtres pour l'extraction et la compression du deuxième harmonique sont examinés.Les simulations révèlent la présence de lobes latéraux axiaux dans la forme d'onde compressée au fur et a mesure que la largeur de bande de la compression d 'impulsion transmise est augmentée.Ces lobes latéraux, dus au chevauchement de la bande harmonique fondamentale et de la troisième bande avec la deuxième bande harmonique ne peuvent pas être enlevés en utilisant le filtrage conventionnel de Fourier.En tant qu'alternative, des techniques de filtrage utilisant la séparation de bandes harmoniques de compressions d 'impulsions rétrodiffusés dans le domaine commun de temps-fréquence sont suggérées.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.003

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 head0.014
GPT teacher head0.288
Teacher spread0.274 · 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

Citations22
Published2007
Admission routes2
Has abstractyes

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