Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling

Pengfei Song; Joshua D Trazasko; Armando Manduca; Bo Qiang; Ramanathan D Kadirvel; David F Kallmes; Shigao D Chen

doi:10.1109/ULTSYM.2017.8092204

Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling

Pengfei Song, Joshua D Trazasko, Armando Manduca, Bo Qiang, Ramanathan D Kadirvel, David F Kallmes, Shigao D Chen

Radiology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Singular value decomposition (SVD)-based clutter filtering has demonstrated superior clutter rejection performance in the emerging field of ultrasound microvessel imaging. To alleviate the computational burden of SVD, here we present a fast and robust clutter filter using randomized SVD (rSVD) and randomized spatial downsampling (rSD). rSVD accelerates SVD by approximating and removing the first k-order singular values that represent tissue, and rSD achieves further speed-up by allowing parallel processing without introducing artifacts associated with regularized downsampling.

Original language	English (US)
Title of host publication	2017 IEEE International Ultrasonics Symposium, IUS 2017
Publisher	IEEE Computer Society
ISBN (Electronic)	9781538633830
DOIs	https://doi.org/10.1109/ULTSYM.2017.8092204
State	Published - Oct 31 2017
Event	2017 IEEE International Ultrasonics Symposium, IUS 2017 - Washington, United States Duration: Sep 6 2017 → Sep 9 2017

Other

Other	2017 IEEE International Ultrasonics Symposium, IUS 2017
Country/Territory	United States
City	Washington
Period	9/6/17 → 9/9/17

ASJC Scopus subject areas

Acoustics and Ultrasonics

Access to Document

10.1109/ULTSYM.2017.8092204

Cite this

Song, P., Trazasko, J. D., Manduca, A., Qiang, B., Kadirvel, R. D., Kallmes, D. F., & Chen, S. D. (2017). Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling. In 2017 IEEE International Ultrasonics Symposium, IUS 2017 [8092204] IEEE Computer Society. https://doi.org/10.1109/ULTSYM.2017.8092204

Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling. / Song, Pengfei ; Trazasko, Joshua D ; Manduca, Armando et al.

2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society, 2017. 8092204.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Song, P , Trazasko, JD , Manduca, A, Qiang, B, Kadirvel, RD , Kallmes, DF & Chen, SD 2017, Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling. in 2017 IEEE International Ultrasonics Symposium, IUS 2017., 8092204, IEEE Computer Society, 2017 IEEE International Ultrasonics Symposium, IUS 2017, Washington, United States, 9/6/17. https://doi.org/10.1109/ULTSYM.2017.8092204

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title = "Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling",

abstract = "Singular value decomposition (SVD)-based clutter filtering has demonstrated superior clutter rejection performance in the emerging field of ultrasound microvessel imaging. To alleviate the computational burden of SVD, here we present a fast and robust clutter filter using randomized SVD (rSVD) and randomized spatial downsampling (rSD). rSVD accelerates SVD by approximating and removing the first k-order singular values that represent tissue, and rSD achieves further speed-up by allowing parallel processing without introducing artifacts associated with regularized downsampling.",

author = "Pengfei Song and Trazasko, {Joshua D} and Armando Manduca and Bo Qiang and Kadirvel, {Ramanathan D} and Kallmes, {David F} and Chen, {Shigao D}",

year = "2017",

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doi = "10.1109/ULTSYM.2017.8092204",

language = "English (US)",

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AU - Qiang, Bo

AU - Kadirvel, Ramanathan D

AU - Kallmes, David F

AU - Chen, Shigao D

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N2 - Singular value decomposition (SVD)-based clutter filtering has demonstrated superior clutter rejection performance in the emerging field of ultrasound microvessel imaging. To alleviate the computational burden of SVD, here we present a fast and robust clutter filter using randomized SVD (rSVD) and randomized spatial downsampling (rSD). rSVD accelerates SVD by approximating and removing the first k-order singular values that represent tissue, and rSD achieves further speed-up by allowing parallel processing without introducing artifacts associated with regularized downsampling.

AB - Singular value decomposition (SVD)-based clutter filtering has demonstrated superior clutter rejection performance in the emerging field of ultrasound microvessel imaging. To alleviate the computational burden of SVD, here we present a fast and robust clutter filter using randomized SVD (rSVD) and randomized spatial downsampling (rSD). rSVD accelerates SVD by approximating and removing the first k-order singular values that represent tissue, and rSD achieves further speed-up by allowing parallel processing without introducing artifacts associated with regularized downsampling.

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PB - IEEE Computer Society

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Y2 - 6 September 2017 through 9 September 2017

ER -

Fast and robust spatiotemporal microvessel clutter filtering with randomized singular value decomposition (rSVD) and randomized spatial downsampling

Abstract

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