Clutter Removing Filter for Ultrasound Blood Flow Imaging Based on Low Rank Model
Du Yigang1,2, Zhang Mengyi3, Chen Siping1*, Li Yong2
1(National-Regional Key Technology Engineering Laboratory for MedicalUltrasound, Department of Biomedical Engineering, School of Medicine, Shenzhen University, Shenzhen 518060, Guangdong, China) 2(Shenzhen Mindray Bio-Medical Electronics Co. Ltd., Shenzhen 518057, Guangdong, China) 3(Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong, China)
Abstract：The conventional ultrasound blood flow wall filter uses a fixed cut-off frequency, which is not effective when the tissue motion is different due to heart beat and breath. This paper presented an ultrasound clutter removing filter based on a low rank model. The characteristics of ultrasound flow signal was studied and formulated. The low rank model was comprised of a rank minimization and matrix sparsity problem. The convex optimization can be applied to solve it after relaxation. The novelty is that it is an adaptive filter due to the minimization of the combination of the nuclear norm and L1 norm. Ultrasound blood flow data were simulated. The filtered signals were obtained by three different orders FIR filters and the low rank filter. The RMS errors for FIR filtering were around 34%, 16% and 12% respectively, and lower than 0.001% when using the low rank filter, which not only improved the accuracy a lot but also maintained the same length of the filtered signal as the original one's, where the length of the FIR filtered signal was decreased compared to the original signal. However, the low rank model is much more complicated than the conventional method, and it is still difficult to be applied in a real-time ultrasound imaging system.
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