Please use this identifier to cite or link to this item:
http://localhost/handle/Hannan/144514
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Siyuan Wei | en_US |
dc.contributor.author | Ming Yang | en_US |
dc.contributor.author | Jian Zhou | en_US |
dc.contributor.author | Richard Sampson | en_US |
dc.contributor.author | Oliver D. Kripfgans | en_US |
dc.contributor.author | J. Brian Fowlkes | en_US |
dc.contributor.author | Thomas F. Wenisch | en_US |
dc.contributor.author | Chaitali Chakrabarti | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-04-06T07:10:27Z | - |
dc.date.available | 2020-04-06T07:10:27Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.other | 10.1109/TUFFC.2017.2676091 | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/144514 | - |
dc.description.abstract | Volumetric 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.extent | 772, | en_US |
dc.format.extent | 784 | en_US |
dc.publisher | IEEE | en_US |
dc.relation.haspart | 7866872.pdf | en_US |
dc.title | Low-Cost 3-D Flow Estimation of Blood With Clutter | en_US |
dc.type | Article | en_US |
dc.journal.volume | 64 | en_US |
dc.journal.issue | 5 | en_US |
Appears in Collections: | 2017 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
7866872.pdf | 2.58 MB | Adobe PDF |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Siyuan Wei | en_US |
dc.contributor.author | Ming Yang | en_US |
dc.contributor.author | Jian Zhou | en_US |
dc.contributor.author | Richard Sampson | en_US |
dc.contributor.author | Oliver D. Kripfgans | en_US |
dc.contributor.author | J. Brian Fowlkes | en_US |
dc.contributor.author | Thomas F. Wenisch | en_US |
dc.contributor.author | Chaitali Chakrabarti | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-04-06T07:10:27Z | - |
dc.date.available | 2020-04-06T07:10:27Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.other | 10.1109/TUFFC.2017.2676091 | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/144514 | - |
dc.description.abstract | Volumetric 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.extent | 772, | en_US |
dc.format.extent | 784 | en_US |
dc.publisher | IEEE | en_US |
dc.relation.haspart | 7866872.pdf | en_US |
dc.title | Low-Cost 3-D Flow Estimation of Blood With Clutter | en_US |
dc.type | Article | en_US |
dc.journal.volume | 64 | en_US |
dc.journal.issue | 5 | en_US |
Appears in Collections: | 2017 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
7866872.pdf | 2.58 MB | Adobe PDF |
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Siyuan Wei | en_US |
dc.contributor.author | Ming Yang | en_US |
dc.contributor.author | Jian Zhou | en_US |
dc.contributor.author | Richard Sampson | en_US |
dc.contributor.author | Oliver D. Kripfgans | en_US |
dc.contributor.author | J. Brian Fowlkes | en_US |
dc.contributor.author | Thomas F. Wenisch | en_US |
dc.contributor.author | Chaitali Chakrabarti | en_US |
dc.date.accessioned | 2013 | en_US |
dc.date.accessioned | 2020-04-06T07:10:27Z | - |
dc.date.available | 2020-04-06T07:10:27Z | - |
dc.date.issued | 2017 | en_US |
dc.identifier.other | 10.1109/TUFFC.2017.2676091 | en_US |
dc.identifier.uri | http://localhost/handle/Hannan/144514 | - |
dc.description.abstract | Volumetric 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.extent | 772, | en_US |
dc.format.extent | 784 | en_US |
dc.publisher | IEEE | en_US |
dc.relation.haspart | 7866872.pdf | en_US |
dc.title | Low-Cost 3-D Flow Estimation of Blood With Clutter | en_US |
dc.type | Article | en_US |
dc.journal.volume | 64 | en_US |
dc.journal.issue | 5 | en_US |
Appears in Collections: | 2017 |
Files in This Item:
File | Size | Format | |
---|---|---|---|
7866872.pdf | 2.58 MB | Adobe PDF |