Low cost clutter filter for 3D ultrasonic flow estimation

3D blood velocity estimation in medical ultrasound systems is revolutionizing the diagnosis of vascular diseases. However, the accuracy of blood velocity estimation is greatly affected by clutter signals from the vessel wall and the tissues surrounding the vessel. Filters used today to remove clutter are computationally expensive, limiting their practicality in portable 3D systems. In this paper, we present clutter filters for arterial flow that reduce computational complexity by orders of magnitude while maintaining the clutter removal performance of existing techniques. We achieve this goal by combining the existing Hankel-SVD clutter filter with the power iteration method to eliminate unnecessary SVD calculations. For the filters which use power iteration exclusively, we achieve excellent filtering performance with only 14.2% computational overhead to our previous flow estimation system. With these filtering methods, our pipelined architecture can compute velocity fields at a rate of 85 frames per second.

[1]  Lasse Lovstakken,et al.  Eigen-based clutter filter design for ultrasound color flow imaging: a review , 2010, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[2]  R. Cobbold,et al.  Single-ensemble-based eigen-processing methods for color flow imaging - Part I. The Hankel-SVD filter , 2008, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[3]  An-Yeu Wu,et al.  Joint-decision adaptive clutter filter and motion-tracking adaptive persistence for Color Doppler processing in ultrasonic systems , 2010, 2010 IEEE Workshop On Signal Processing Systems.

[4]  J. Arendt Paper presented at the 10th Nordic-Baltic Conference on Biomedical Imaging: Field: A Program for Simulating Ultrasound Systems , 1996 .

[5]  J. Jensen,et al.  Recent advances in blood flow vector velocity imaging , 2011, 2011 IEEE International Ultrasonics Symposium.

[6]  H. Torp,et al.  Clutter filters adapted to tissue motion in ultrasound color flow imaging , 2002, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[7]  Ming Yang,et al.  A low complexity scheme for accurate 3D velocity estimation in ultrasound systems , 2014, 2014 IEEE Workshop on Signal Processing Systems (SiPS).

[8]  R. Cobbold Foundations of Biomedical Ultrasound , 2006 .

[9]  J. Rubin,et al.  Measurement of Volumetric Flow , 2006, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[10]  K. Boone,et al.  Effect of skin impedance on image quality and variability in electrical impedance tomography: a model study , 1996, Medical and Biological Engineering and Computing.

[11]  Ming Yang,et al.  Separable Beamforming For 3-D Medical Ultrasound Imaging , 2015, IEEE Transactions on Signal Processing.

[12]  L. Thomas,et al.  An improved wall filter for flow imaging of low velocity flow , 1994, 1994 Proceedings of IEEE Ultrasonics Symposium.

[13]  J. Jensen,et al.  Calculation of pressure fields from arbitrarily shaped, apodized, and excited ultrasound transducers , 1992, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[14]  Gene H. Golub,et al.  Matrix computations , 1983 .

[15]  Ming Yang,et al.  High Frame Rate 3-D Ultrasound Imaging Using Separable Beamforming , 2015, J. Signal Process. Syst..