Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/144514
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dc.contributor.authorSiyuan Weien_US
dc.contributor.authorMing Yangen_US
dc.contributor.authorJian Zhouen_US
dc.contributor.authorRichard Sampsonen_US
dc.contributor.authorOliver D. Kripfgansen_US
dc.contributor.authorJ. Brian Fowlkesen_US
dc.contributor.authorThomas F. Wenischen_US
dc.contributor.authorChaitali Chakrabartien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:10:27Z-
dc.date.available2020-04-06T07:10:27Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TUFFC.2017.2676091en_US
dc.identifier.urihttp://localhost/handle/Hannan/144514-
dc.description.abstractVolumetric flow rate estimation is an important ultrasound medical imaging modality that is used for diagnosing cardiovascular diseases. Flow rates are obtained by integrating velocity estimates over a cross-sectional plane. Speckle tracking is a promising approach that overcomes the angle dependency of traditional Doppler methods, but suffers from poor lateral resolution. Recent work improves lateral velocity estimation accuracy by reconstructing a synthetic lateral phase (SLP) signal. However, the estimation accuracy of such approaches is compromised by the presence of clutter. Eigen-based clutter filtering has been shown to be effective in removing the clutter signal; but it is computationally expensive, precluding its use at high volume rates. In this paper, we propose low-complexity schemes for both velocity estimation and clutter filtering. We use a two-tiered motion estimation scheme to combine the low complexity sum-of-absolute-difference and SLP methods to achieve subpixel lateral accuracy. We reduce the complexity of eigen-based clutter filtering by processing in subgroups and replacing singular value decomposition with less compute-intensive power iteration and subspace iteration methods. Finally, to improve flow rate estimation accuracy, we use kernel power weighting when integrating the velocity estimates. We evaluate our method for fast- and slow-moving clutter for beam-to-flow angles of 90&x00B0; and 60&x00B0; using Field II simulations, demonstrating high estimation accuracy across scenarios. For instance, for a beam-to-flow angle of 90&x00B0; and fast-moving clutter, our estimation method provides a bias of -8.8% and standard deviation of 3.1% relative to the actual flow rate.en_US
dc.format.extent772,en_US
dc.format.extent784en_US
dc.publisherIEEEen_US
dc.relation.haspart7866872.pdfen_US
dc.titleLow-Cost 3-D Flow Estimation of Blood With Clutteren_US
dc.typeArticleen_US
dc.journal.volume64en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7866872.pdf2.58 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSiyuan Weien_US
dc.contributor.authorMing Yangen_US
dc.contributor.authorJian Zhouen_US
dc.contributor.authorRichard Sampsonen_US
dc.contributor.authorOliver D. Kripfgansen_US
dc.contributor.authorJ. Brian Fowlkesen_US
dc.contributor.authorThomas F. Wenischen_US
dc.contributor.authorChaitali Chakrabartien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:10:27Z-
dc.date.available2020-04-06T07:10:27Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TUFFC.2017.2676091en_US
dc.identifier.urihttp://localhost/handle/Hannan/144514-
dc.description.abstractVolumetric flow rate estimation is an important ultrasound medical imaging modality that is used for diagnosing cardiovascular diseases. Flow rates are obtained by integrating velocity estimates over a cross-sectional plane. Speckle tracking is a promising approach that overcomes the angle dependency of traditional Doppler methods, but suffers from poor lateral resolution. Recent work improves lateral velocity estimation accuracy by reconstructing a synthetic lateral phase (SLP) signal. However, the estimation accuracy of such approaches is compromised by the presence of clutter. Eigen-based clutter filtering has been shown to be effective in removing the clutter signal; but it is computationally expensive, precluding its use at high volume rates. In this paper, we propose low-complexity schemes for both velocity estimation and clutter filtering. We use a two-tiered motion estimation scheme to combine the low complexity sum-of-absolute-difference and SLP methods to achieve subpixel lateral accuracy. We reduce the complexity of eigen-based clutter filtering by processing in subgroups and replacing singular value decomposition with less compute-intensive power iteration and subspace iteration methods. Finally, to improve flow rate estimation accuracy, we use kernel power weighting when integrating the velocity estimates. We evaluate our method for fast- and slow-moving clutter for beam-to-flow angles of 90&x00B0; and 60&x00B0; using Field II simulations, demonstrating high estimation accuracy across scenarios. For instance, for a beam-to-flow angle of 90&x00B0; and fast-moving clutter, our estimation method provides a bias of -8.8% and standard deviation of 3.1% relative to the actual flow rate.en_US
dc.format.extent772,en_US
dc.format.extent784en_US
dc.publisherIEEEen_US
dc.relation.haspart7866872.pdfen_US
dc.titleLow-Cost 3-D Flow Estimation of Blood With Clutteren_US
dc.typeArticleen_US
dc.journal.volume64en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7866872.pdf2.58 MBAdobe PDF
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSiyuan Weien_US
dc.contributor.authorMing Yangen_US
dc.contributor.authorJian Zhouen_US
dc.contributor.authorRichard Sampsonen_US
dc.contributor.authorOliver D. Kripfgansen_US
dc.contributor.authorJ. Brian Fowlkesen_US
dc.contributor.authorThomas F. Wenischen_US
dc.contributor.authorChaitali Chakrabartien_US
dc.date.accessioned2013en_US
dc.date.accessioned2020-04-06T07:10:27Z-
dc.date.available2020-04-06T07:10:27Z-
dc.date.issued2017en_US
dc.identifier.other10.1109/TUFFC.2017.2676091en_US
dc.identifier.urihttp://localhost/handle/Hannan/144514-
dc.description.abstractVolumetric flow rate estimation is an important ultrasound medical imaging modality that is used for diagnosing cardiovascular diseases. Flow rates are obtained by integrating velocity estimates over a cross-sectional plane. Speckle tracking is a promising approach that overcomes the angle dependency of traditional Doppler methods, but suffers from poor lateral resolution. Recent work improves lateral velocity estimation accuracy by reconstructing a synthetic lateral phase (SLP) signal. However, the estimation accuracy of such approaches is compromised by the presence of clutter. Eigen-based clutter filtering has been shown to be effective in removing the clutter signal; but it is computationally expensive, precluding its use at high volume rates. In this paper, we propose low-complexity schemes for both velocity estimation and clutter filtering. We use a two-tiered motion estimation scheme to combine the low complexity sum-of-absolute-difference and SLP methods to achieve subpixel lateral accuracy. We reduce the complexity of eigen-based clutter filtering by processing in subgroups and replacing singular value decomposition with less compute-intensive power iteration and subspace iteration methods. Finally, to improve flow rate estimation accuracy, we use kernel power weighting when integrating the velocity estimates. We evaluate our method for fast- and slow-moving clutter for beam-to-flow angles of 90&x00B0; and 60&x00B0; using Field II simulations, demonstrating high estimation accuracy across scenarios. For instance, for a beam-to-flow angle of 90&x00B0; and fast-moving clutter, our estimation method provides a bias of -8.8% and standard deviation of 3.1% relative to the actual flow rate.en_US
dc.format.extent772,en_US
dc.format.extent784en_US
dc.publisherIEEEen_US
dc.relation.haspart7866872.pdfen_US
dc.titleLow-Cost 3-D Flow Estimation of Blood With Clutteren_US
dc.typeArticleen_US
dc.journal.volume64en_US
dc.journal.issue5en_US
Appears in Collections:2017

Files in This Item:
File SizeFormat 
7866872.pdf2.58 MBAdobe PDF