Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction.
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| Title: | Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction. |
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| Authors: | Besson, Adrien1, Perdios, Dimitris1, Martinez, Florian1, Chen, Zhouye2, Carrillo, Rafael E.3, Arditi, Marcel1, Wiaux, Yves2, Thiran, Jean-Philippe1 |
| Source: | IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control. Mar2018, Vol. 65 Issue 3, p339-355. 17p. |
| Subjects: | Ultrasonic imaging, Image reconstruction, Beamforming, Inverse problems, Image quality analysis |
| Abstract: | Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution to the image reconstruction problem. An alternative to DAS consists in using iterative techniques, which require both an accurate measurement model and a strong prior on the image under scrutiny. Toward this goal, much effort has been deployed in formulating models for US imaging, which usually require a large amount of memory to store the matrix coefficients. We present two different techniques, which take advantage of fast and matrix-free formulations derived for the measurement model and its adjoint, and rely on sparsity of US images in well-chosen models. Sparse regularization is used for enhanced image reconstruction. Compressed beamforming exploits the compressed sensing framework to restore high-quality images from fewer raw data than state-of-the-art approaches. Using simulated data and in vivo experimental acquisitions, we show that the proposed approach is three orders of magnitude faster than non-DAS state-of-the-art methods, with comparable or better image quality. [ABSTRACT FROM PUBLISHER] |
| Copyright of IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 128321689 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Besson%2C+Adrien%22">Besson, Adrien</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Perdios%2C+Dimitris%22">Perdios, Dimitris</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Martinez%2C+Florian%22">Martinez, Florian</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Zhouye%22">Chen, Zhouye</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Carrillo%2C+Rafael+E%2E%22">Carrillo, Rafael E.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Arditi%2C+Marcel%22">Arditi, Marcel</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Wiaux%2C+Yves%22">Wiaux, Yves</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Thiran%2C+Jean-Philippe%22">Thiran, Jean-Philippe</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IEEE+Transactions+on+Ultrasonics+Ferroelectrics+%26+Frequency+Control%22">IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control</searchLink>. Mar2018, Vol. 65 Issue 3, p339-355. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Ultrasonic+imaging%22">Ultrasonic imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Image+reconstruction%22">Image reconstruction</searchLink><br /><searchLink fieldCode="DE" term="%22Beamforming%22">Beamforming</searchLink><br /><searchLink fieldCode="DE" term="%22Inverse+problems%22">Inverse problems</searchLink><br /><searchLink fieldCode="DE" term="%22Image+quality+analysis%22">Image quality analysis</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution to the image reconstruction problem. An alternative to DAS consists in using iterative techniques, which require both an accurate measurement model and a strong prior on the image under scrutiny. Toward this goal, much effort has been deployed in formulating models for US imaging, which usually require a large amount of memory to store the matrix coefficients. We present two different techniques, which take advantage of fast and matrix-free formulations derived for the measurement model and its adjoint, and rely on sparsity of US images in well-chosen models. Sparse regularization is used for enhanced image reconstruction. Compressed beamforming exploits the compressed sensing framework to restore high-quality images from fewer raw data than state-of-the-art approaches. Using simulated data and in vivo experimental acquisitions, we show that the proposed approach is three orders of magnitude faster than non-DAS state-of-the-art methods, with comparable or better image quality. [ABSTRACT FROM PUBLISHER] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1109/TUFFC.2017.2768583 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 339 Subjects: – SubjectFull: Ultrasonic imaging Type: general – SubjectFull: Image reconstruction Type: general – SubjectFull: Beamforming Type: general – SubjectFull: Inverse problems Type: general – SubjectFull: Image quality analysis Type: general Titles: – TitleFull: Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Besson, Adrien – PersonEntity: Name: NameFull: Perdios, Dimitris – PersonEntity: Name: NameFull: Martinez, Florian – PersonEntity: Name: NameFull: Chen, Zhouye – PersonEntity: Name: NameFull: Carrillo, Rafael E. – PersonEntity: Name: NameFull: Arditi, Marcel – PersonEntity: Name: NameFull: Wiaux, Yves – PersonEntity: Name: NameFull: Thiran, Jean-Philippe IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: Mar2018 Type: published Y: 2018 Identifiers: – Type: issn-print Value: 08853010 Numbering: – Type: volume Value: 65 – Type: issue Value: 3 Titles: – TitleFull: IEEE Transactions on Ultrasonics Ferroelectrics & Frequency Control Type: main |
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