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Record W2160847388 · doi:10.1109/ultsym.2009.5441887

A novel technique for measuring ultrasound backscatter from single micron-sized objects

2009· article· en· W2160847388 on OpenAlexafffundabout
Omar Falou, Ahmed El-Kaffas, J. Carl Kumaradas, Michael C. Kolios

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
Topic3D Printing in Biomedical Research
Canadian institutionsToronto Metropolitan University
FundersCanada Research Chairs
KeywordsBackscatter (email)TransducerMaterials scienceMicroscopeUltrasoundUltrasonic sensorOpticsPipetteLens (geology)SIGNAL (programming language)Optical microscopeAcousticsRangingFocal lengthBiomedical engineeringComputer sciencePhysicsScanning electron microscopeChemistryTelecommunications

Abstract

fetched live from OpenAlex

The measurement of the ultrasound backscatter from individual micron-sized objects is required to gain an understanding of the behavior of both weak (cells) and strong (contrast agents) scatterers for applications ranging from tissue characterization to molecular imaging. However, obtaining such a response remains a challenge. For instance, the presence of air bubbles in a suspension of cells during measurements of cell backscatter may lead to the incorrect interpretation of the backscattered signals. In addition, the size and shape of the single object that produces an ultrasound backscatter signal are critical input parameters to theoretical models, yet hard to be measured experimentally. In this work, a novel technique combining a Xenoworks microinjection system (Sutter, Inc., Los Angeles, CA) with co-registered Olympus IX71 inverted microscope (Olympus America, Inc., Center Valley, PA) and a VEVO770 Ultrasound imaging device (VisualSonics, Inc., Toronto, ON) was developed in which the ultrasound backscatter response from a single object was obtained under optical microscope guidance. This technique provides accurate information about the size and shape of the object. Two transducers of central frequencies of 25 and 55 MHz were used (for a total spectrum of 12-57 MHz). The foci of the optical lens and the transducer were aligned to obtain optical and ultrasonic images of the same region. The object of interest was attached to the micropipette (using negative pressure) and then released from the micropipette (using positive pressure and/or tapping on the micropipette) while imaging it both optically and ultrasonically. In order to calibrate the system, a micropipette was used to grab a 20 ?m polystyrene microsphere from a suspension of microspheres in degassed water by applying a pressure of -18.9 kPa. The microsphere was released by applying a pressure of +35.0 kPa. During the release, optical and ultrasonic raw RF lines were obtained. These lines were then used to obtain the power spectral plot of individual microspheres which were compared to analytical solutions. A very good agreement was found (error of 1%) between the measured backscatter response of microspheres and that of a Faran model of an elastic sphere. Extension of this method to prostate carcinoma (PC-3) cells showed a good agreement (error of 5%) when compared to the Anderson fluid sphere model. This technique is capable of providing accurate measurements of the backscatter from individual objects and is currently being used to deduce the backscatter response from other cell lines of different sizes and from ultrasound contrast agents either in isolation or when attached to a cell. The advantages of the technique along with its future applications are discussed.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.032
GPT teacher head0.260
Teacher spread0.229 · 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

Citations5
Published2009
Admission routes3
Has abstractyes

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