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Article: Single-ensemble-based eigen-processing methods for color flow imaging-Part II. the matrix pencil estimator

TitleSingle-ensemble-based eigen-processing methods for color flow imaging-Part II. the matrix pencil estimator
Authors
Issue Date2008
PublisherIEEE.
Citation
Ieee Transactions On Ultrasonics, Ferroelectrics, And Frequency Control, 2008, v. 55 n. 3, p. 573-587 How to Cite?
AbstractParametric spectral estimators can potentially be used to obtain flow estimates directly from raw slow-time ensembles whose clutter has not been suppressed. We present a new eigen-based parametric flow estimation method called the matrix pencil, whose principles are based on a matrix form under the same name. The presented method models the slow-time signal as a sum of dominant complex sinusoids in the slow-time ensemble, and it computes the principal Doppler frequencies by using a generalized eigenvalue problem formulation and matrix rank reduction principles. Both fixed-rank (rank-one, rank-two) and adaptive-rank matrix pencil flow estimators are proposed, and their potential applicability to color flow signal processing is discussed. For the adaptive-rank estimator, the nominal rank was defined as the minimum eigen-structure rank that yields principal frequency estimates with a spread greater than a prescribed bandwidth. In our initial performance evaluation, the fixed-rank matrix pencil estimators were applied to raw color flow data (transmit frequency: 5 MHz; pulse repetition period: 0.175 ms; ensemble size: 14) acquired from a steady flow phantom (70 cm/s at centerline) that was surrounded by rigid-tissue-mimicking material. These fixed-rank estimators produced velocity maps that are well correlated with the theoretical flow profile (correlation coefficient: 0.964 to 0.975). To facilitate further evaluation, the matrix pencil estimators were applied to synthetic slow-time data (transmit frequency: 5 MHz; pulse repetition period: 1.0 ms; ensemble size: 10) modeling flow scenarios without and with tissue motion (up to 1 cm/s). The bias and root-mean-squared error of the estimators were computed as a function of blood-signal-to-noise ratio and blood velocity. The matrix pencil flow estimators showed that they are comparatively less biased than most of the existing frequency-based flow estimators like the lag-one autocorrelator. © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/57477
ISSN
2015 Impact Factor: 2.287
2015 SCImago Journal Rankings: 0.910
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYu, ACHen_HK
dc.contributor.authorCobbold, RSCen_HK
dc.date.accessioned2010-04-12T01:37:37Z-
dc.date.available2010-04-12T01:37:37Z-
dc.date.issued2008en_HK
dc.identifier.citationIeee Transactions On Ultrasonics, Ferroelectrics, And Frequency Control, 2008, v. 55 n. 3, p. 573-587en_HK
dc.identifier.issn0885-3010en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57477-
dc.description.abstractParametric spectral estimators can potentially be used to obtain flow estimates directly from raw slow-time ensembles whose clutter has not been suppressed. We present a new eigen-based parametric flow estimation method called the matrix pencil, whose principles are based on a matrix form under the same name. The presented method models the slow-time signal as a sum of dominant complex sinusoids in the slow-time ensemble, and it computes the principal Doppler frequencies by using a generalized eigenvalue problem formulation and matrix rank reduction principles. Both fixed-rank (rank-one, rank-two) and adaptive-rank matrix pencil flow estimators are proposed, and their potential applicability to color flow signal processing is discussed. For the adaptive-rank estimator, the nominal rank was defined as the minimum eigen-structure rank that yields principal frequency estimates with a spread greater than a prescribed bandwidth. In our initial performance evaluation, the fixed-rank matrix pencil estimators were applied to raw color flow data (transmit frequency: 5 MHz; pulse repetition period: 0.175 ms; ensemble size: 14) acquired from a steady flow phantom (70 cm/s at centerline) that was surrounded by rigid-tissue-mimicking material. These fixed-rank estimators produced velocity maps that are well correlated with the theoretical flow profile (correlation coefficient: 0.964 to 0.975). To facilitate further evaluation, the matrix pencil estimators were applied to synthetic slow-time data (transmit frequency: 5 MHz; pulse repetition period: 1.0 ms; ensemble size: 10) modeling flow scenarios without and with tissue motion (up to 1 cm/s). The bias and root-mean-squared error of the estimators were computed as a function of blood-signal-to-noise ratio and blood velocity. The matrix pencil flow estimators showed that they are comparatively less biased than most of the existing frequency-based flow estimators like the lag-one autocorrelator. © 2006 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Controlen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshBlood Flow Velocity - physiologyen_HK
dc.subject.meshCoronary Circulation - physiologyen_HK
dc.subject.meshCoronary Vessels - ultrasonographyen_HK
dc.subject.meshEchocardiography, Doppler, Color - instrumentation - methodsen_HK
dc.titleSingle-ensemble-based eigen-processing methods for color flow imaging-Part II. the matrix pencil estimatoren_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0885-3010&volume=55&issue=3&spage=573&epage=587&date=2008&atitle=Single-ensemble-based+eigen-processing+methods+for+color+flow+imaging—Part+II.+The+matrix+pencil+estimatoren_HK
dc.identifier.emailYu, ACH:alfred.yu@hku.hken_HK
dc.identifier.authorityYu, ACH=rp00657en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TUFFC.2008.683en_HK
dc.identifier.pmid18407848-
dc.identifier.scopuseid_2-s2.0-44849128368en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-44849128368&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume55en_HK
dc.identifier.issue3en_HK
dc.identifier.spage573en_HK
dc.identifier.epage587en_HK
dc.identifier.isiWOS:000254118500005-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYu, ACH=8699317700en_HK
dc.identifier.scopusauthoridCobbold, RSC=7005052711en_HK

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