Singular value decomposition-based noise equalization for ultrafast plane wave microvessel imaging

Pengfei Song; Armando Manduca; Joshua D. Trzasko; Shigao Chen

doi:10.1109/ULTSYM.2017.8091722

Singular value decomposition-based noise equalization for ultrafast plane wave microvessel imaging

Pengfei Song, Armando Manduca, Joshua D. Trzasko, Shigao Chen

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

Abstract

Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity. The rich spatiotemporal plane wave data enables robust clutter filtering based on singular value decomposition (SVD). However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. The mid-to-deep region of the microvessel image is typically saturated by noise, hampering the visibility of microvessels. This study was designed to: 1) study the fundamental relationship between ultrasound system noise and microvessel signal; 2) propose an adaptive and computationally cost-effective noise equalization method derived from the SVD clutter filtering process to improve microvessel image quality.

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.2017.8091722
State	Published - Oct 31 2017
Event	2017 IEEE International Ultrasonics Symposium, IUS 2017 - Washington, United States Duration: Sep 6 2017 → Sep 9 2017

Publication series

Name	IEEE International Ultrasonics Symposium, IUS
ISSN (Print)	1948-5719
ISSN (Electronic)	1948-5727

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.2017.8091722

Cite this

Singular value decomposition-based noise equalization for ultrafast plane wave microvessel imaging. / Song, Pengfei ; Manduca, Armando ; Trzasko, Joshua D. et al.
2017 IEEE International Ultrasonics Symposium, IUS 2017. IEEE Computer Society, 2017. 8091722 (IEEE International Ultrasonics Symposium, IUS).

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

Song, P , Manduca, A , Trzasko, JD & Chen, S 2017, Singular value decomposition-based noise equalization for ultrafast plane wave microvessel imaging. in 2017 IEEE International Ultrasonics Symposium, IUS 2017., 8091722, IEEE International Ultrasonics Symposium, IUS, IEEE Computer Society, 2017 IEEE International Ultrasonics Symposium, IUS 2017, Washington, United States, 9/6/17. https://doi.org/10.1109/ULTSYM.2017.8091722

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title = "Singular value decomposition-based noise equalization for ultrafast plane wave microvessel imaging",

abstract = "Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity. The rich spatiotemporal plane wave data enables robust clutter filtering based on singular value decomposition (SVD). However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. The mid-to-deep region of the microvessel image is typically saturated by noise, hampering the visibility of microvessels. This study was designed to: 1) study the fundamental relationship between ultrasound system noise and microvessel signal; 2) propose an adaptive and computationally cost-effective noise equalization method derived from the SVD clutter filtering process to improve microvessel image quality.",

author = "Pengfei Song and Armando Manduca and Trzasko, {Joshua D.} and Shigao Chen",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 2017 IEEE International Ultrasonics Symposium, IUS 2017 ; Conference date: 06-09-2017 Through 09-09-2017",

year = "2017",

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day = "31",

doi = "10.1109/ULTSYM.2017.8091722",

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N2 - Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity. The rich spatiotemporal plane wave data enables robust clutter filtering based on singular value decomposition (SVD). However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. The mid-to-deep region of the microvessel image is typically saturated by noise, hampering the visibility of microvessels. This study was designed to: 1) study the fundamental relationship between ultrasound system noise and microvessel signal; 2) propose an adaptive and computationally cost-effective noise equalization method derived from the SVD clutter filtering process to improve microvessel image quality.

AB - Ultrafast plane wave microvessel imaging significantly improves ultrasound Doppler sensitivity. The rich spatiotemporal plane wave data enables robust clutter filtering based on singular value decomposition (SVD). However, due to the lack of transmit focusing, plane wave microvessel imaging is very susceptible to noise. The mid-to-deep region of the microvessel image is typically saturated by noise, hampering the visibility of microvessels. This study was designed to: 1) study the fundamental relationship between ultrasound system noise and microvessel signal; 2) propose an adaptive and computationally cost-effective noise equalization method derived from the SVD clutter filtering process to improve microvessel image quality.

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Singular value decomposition-based noise equalization for ultrafast plane wave microvessel imaging

Abstract

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