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

Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish (US)
Title of host publication2017 IEEE International Ultrasonics Symposium, IUS 2017
PublisherIEEE Computer Society
ISBN (Electronic)9781538633830
DOIs
StatePublished - Oct 31 2017
Event2017 IEEE International Ultrasonics Symposium, IUS 2017 - Washington, United States
Duration: Sep 6 2017Sep 9 2017

Other

Other2017 IEEE International Ultrasonics Symposium, IUS 2017
CountryUnited States
CityWashington
Period9/6/179/9/17

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ASJC Scopus subject areas

  • Acoustics and Ultrasonics

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