TY - JOUR
T1 - Parallel Implementation of Randomized Singular Value Decomposition and Randomized Spatial Downsampling for Real Time Ultrafast Microvessel Imaging on a Multi-Core CPUs Architecture
AU - Lok, U. Wai
AU - Song, Pengfei
AU - Trzasko, Joshua D.
AU - Borisch, Eric A.
AU - Daigle, Ron
AU - Chen, Shigao
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018
Y1 - 2018
N2 - Singular value decomposition (SVD)-based clutter filter is widely used for functional ultrasound imaging such as super-resolution ultrasound localized microscopy and microvessel imaging. However, the demand of high computational complexity becomes one of the critical issues for the SVD-based clutter filter. Recently, randomized SVD-based (rSVD) clutter filter has been proposed for clutter suppression; the computational time can be dramatically reduced when combing with randomized spatial downsampling. In this study, we propose the use of multicore CPU architecture to implement the rSVD-based clutter filter with randomized spatial downsampling to demonstrate that it can perform in real time. The proposed multi-core CPU architecture was embedded as an external function on a Verasonics Vantage system (Verasonics Inc., Kirkland, WA, USA). As the number of ensembles and the rank of tissue subspace are set as 50 and 20, respectively, the corresponding processing time required only around 20 ms. In addition, we also demonstrated the feasibility of real time microvessel perfusion imaging by rSVD-based clutter filter and random spatial downsampling.
AB - Singular value decomposition (SVD)-based clutter filter is widely used for functional ultrasound imaging such as super-resolution ultrasound localized microscopy and microvessel imaging. However, the demand of high computational complexity becomes one of the critical issues for the SVD-based clutter filter. Recently, randomized SVD-based (rSVD) clutter filter has been proposed for clutter suppression; the computational time can be dramatically reduced when combing with randomized spatial downsampling. In this study, we propose the use of multicore CPU architecture to implement the rSVD-based clutter filter with randomized spatial downsampling to demonstrate that it can perform in real time. The proposed multi-core CPU architecture was embedded as an external function on a Verasonics Vantage system (Verasonics Inc., Kirkland, WA, USA). As the number of ensembles and the rank of tissue subspace are set as 50 and 20, respectively, the corresponding processing time required only around 20 ms. In addition, we also demonstrated the feasibility of real time microvessel perfusion imaging by rSVD-based clutter filter and random spatial downsampling.
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U2 - 10.1109/ULTSYM.2018.8579678
DO - 10.1109/ULTSYM.2018.8579678
M3 - Conference article
AN - SCOPUS:85062544036
SN - 1948-5719
VL - 2018-January
JO - IEEE International Ultrasonics Symposium, IUS
JF - IEEE International Ultrasonics Symposium, IUS
M1 - 8579678
T2 - 2018 IEEE International Ultrasonics Symposium, IUS 2018
Y2 - 22 October 2018 through 25 October 2018
ER -