Adaptive Spatiotemporal Clutter Rejection Based on Casorati-Singular Value Decompositionfor Ultrafast Plane-wave Doppler Imaging

Yiwen XU; Chen YANG; Jie XU; Yang JIAO; Yaoyao CUI

doi:10.11999/JEIT200618

Volume 43 Issue 8

Aug. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(8): 2334-2342

Yiwen XU, Chen YANG, Jie XU, Yang JIAO, Yaoyao CUI. Adaptive Spatiotemporal Clutter Rejection Based on Casorati-Singular Value Decompositionfor Ultrafast Plane-wave Doppler Imaging[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2334-2342. doi: 10.11999/JEIT200618

Citation:

Yiwen XU, Chen YANG, Jie XU, Yang JIAO, Yaoyao CUI. Adaptive Spatiotemporal Clutter Rejection Based on Casorati-Singular Value Decompositionfor Ultrafast Plane-wave Doppler Imaging[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2334-2342. doi: 10.11999/JEIT200618

Citation:

Yiwen XU, Chen YANG, Jie XU, Yang JIAO, Yaoyao CUI. Adaptive Spatiotemporal Clutter Rejection Based on Casorati-Singular Value Decompositionfor Ultrafast Plane-wave Doppler Imaging[J]. Journal of Electronics & Information Technology, 2021, 43(8): 2334-2342. doi: 10.11999/JEIT200618

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Adaptive Spatiotemporal Clutter Rejection Based on Casorati-Singular Value Decompositionfor Ultrafast Plane-wave Doppler Imaging

doi: 10.11999/JEIT200618 cstr: 32379.14.JEIT200618

Yiwen XU¹,
Chen YANG^{2, 3},
Jie XU^{2, 4},
Yang JIAO^{2
,
,},
Yaoyao CUI²

1.
Suzhou GuoKe Ultra Medical Technology Co. Ltd, Suzhou 215163, China
2.
Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
3.
Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei 230031, China
4.
Academy for Engineering and Technology, Fudan University, Shanghai 200433, China

Funds: The National Natural Science Foundation of China (51805529); Jiangsu Provincial Key Research and Development Plan (BE2017601, BE2017661)

Received Date: 2020-07-24
Rev Recd Date: 2021-03-19

Available Online: 2021-04-13

Publish Date: 2021-08-10

Abstract

Abstract

By using compounded plane wave, it enables the high-frame-rate acquisition of synchronous ultrasonic samples in the all field of view. However, classical clutter filters fail to deal with these big synchronous imaging datasets. In this study, an improved adaptive clutter rejection algorithm based on Casorati Singular Value Decomposition (Casorati-SVD) is proposed to take full advantage of synchronous datasets. The first step is to construct a Casorati matrix based on a block of plane-wave data and perform singular value decomposition on this Casorati matrix. Then the key point is to adaptively determine the cufoff thresholds according to Doppler frequency and energy of component signals and the blood flow signal is extracted through auto-generated filter. Finally, adaptive SVD filtering on each block is performed and the final flow signals are reconstructed from all blocks. To assess its ability in noise suppression, the proposed method is applied to blood flow echos obtained from phantom, arm artery and rabbit brain. These results demonstrate the improved method has 4.4% to 50% higher Signal-to-Noise-Ratio (SNR) and 4.7% to 55.9% Contrast-to-Noise-Ratio (CNR) than conventional Casorati-SVD methods. In conclusion, this method realizes spatial adaptive filtering and can be significant for development of clinical blood flow imaging.
- Ultrafast ultrasound plane wave,
- Power Doppler,
- Casorati Singular Value Decomposition (SVD),
- Adaptive clutter suppression

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References(28)

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