Clutter Filtering for Diagnostic Ultrasound Color Flow Imaging
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Clutter filtering plays an important role in constructing a quality color flow map in ultrasound Doppler imaging. Signals from slow-moving tissues and vessel walls are clutter as they often mix with reflections from blood and should be suppressed for the further correct estimation of flow parameters. Their complete suppression in color flow imaging is difficult, because these signals on average are 40-60 dB more powerful than the signals from blood, the length of the Doppler sequence is very short, and there is always a demand for a real-time operation. This article provides a general model of the Doppler signal and discusses filters based on polynomial and adaptive regression, empirical mode decomposition, and prospective combined approaches to blood flow filtering.
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- 3.Yu, A. C. H., Johnston, K. W., and Cobbold, R., S. C., “Frequency-based signal processing for ultrasound color flow imaging,” Canad. Acoust., 35, No. 2, 11-23 (2007).Google Scholar
- 4.Shen, Z., Feng, N., Shen, Y., and Lee, C. H., “An improved para-metric relaxation approach to blood flow signal estimation with single-ensemble in color flow imaging,” J. Med. Biomed. Eng., 33, No. 3, 309-318 (2013).Google Scholar
- 6.Yu, A. C. H. and Lovstakken, L., “Eigen-based clutter filter design for ultrasound color flow imaging: A review,” IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., No. 5, 1096 (2010).Google Scholar
- 7.Yu, A. C. H. and Cobbold, R. S. C., “Single-ensemble-based Eigen-processing methods for color flow imaging – Part, I., The Hankel-SVD Filter,” IEEE Trans. Ultrason. Ferroelectr. Freq. Contr., No. 3, 559-572 (2008).Google Scholar
- 9.Wang, P. D., Shen, Y., and Feng, N. Z., “A novel clutter rejection scheme in color flow imaging,” Ultrasonics, No. 44, Supplement 1, e303-e305 (2006).Google Scholar
- 10.Bjærum, S. and Torp, H., “Statistical evaluation of clutter filters in color flow imaging,” Ultrasonics, No. 38, 376-380 (2000).Google Scholar
- 14.Lovstakken, L., Signal Processing in Diagnostic Ultrasound: Algorithms for Real-Time Estimation and Visualization of Blood Flow Velocity, Doctoral Thesis, Norwegian University of Science and Technology (2007).Google Scholar
- 15.Shen, Z., Feng, N., and Shen, Y., “A forward-backward subsequence smoothing eigen-based approach to designing clutter rejection filters in color flow imaging,” IEEE Proc., 43, 535-538 (2014).Google Scholar
- 16.Park, G., Kim, Y., Shim, H., Koh, H. W., Lim, H., Lee, J. J., Yeo, S., Song, T. K., and Yoo, Y., “New adaptive clutter rejection based on spectral decomposition and tissue acceleration for ultrasound color Doppler imaging,” IEEE Ultrason. Symp., 1484-1487 (2014).Google Scholar
- 19.Khan, I. A., Hamid, E., and Nakai, T., “Systolic phase detection from pulsed Doppler ultrasound signal using EMD_DHT based approach,” Int. j. Signal Proc. Image. Proc. Pattern Recogn., 7, No. 5, 207-216 (2014).Google Scholar
- 20.Lo, M. T., Hu, K., Peng, C. K., and Novak, V., “Multimodal pressure flow analysis: application of Hilbert Huang transform in cerebral blood flow regulation,” EURASIP J., Adv. Signal Process., Article id: 785243 (2008).Google Scholar
- 21.Boronoev, B. B. and Omnokov, V. D., “Empirical mode decomposition of pulsed signals. Ground cover probing with radar and synthetic aperture radiometers,” MNTK (2013); http://ipms.bsc-net.ru/conferenc/RS2013/ru/docs/papers/a04.pdf.
- 22.Davydov, A. V., “The Hilbert-Huang transform,” http://geoin.org/hht (date accessed: June 1, 2018).
- 23.Shen, Z. and Lee, C. H., “LASSO based ensemble empirical mode decomposition approach to designing adaptive clutter suppression filters,” Proc. IEEE Acoust. Speech Signal Proc. (ICASSP), 757-760 (2012).Google Scholar
- 26.Torres, S., Ground Clutter Cancelling with a Regression Filter, National Severe Storms Lab. Interim Report, Oklahoma, October 1998.Google Scholar
- 27.Zhou, X., Zhang, C., and Liu, D. C., “Adaptive clutter filter in 2D color flow imaging based on in vivo I/Q signal,” Biomed. Mater. Eng., 24, No. 1, 307-313 (2014).Google Scholar
- 28.Gerbands, J. J., “On the relationships between SVD, KLT and PCA,” Pattern Recognition, No. 14, 375-381 (1981).Google Scholar
- 29.Zobly, A. M. S. and Kadah, Y. M., “A new clutter rejection technique for Doppler ultrasound signal based on principal and independent component analyses,” in: Cairo International Biomedical Engineering Conference (CIBEC) (2012), pp. 56-59.Google Scholar
- 30.Baranger, J., Arnal, B., Perren, F., Baud, O., Tanter, M., and Demené, C., “Adaptive spatiotemporal SVD clutter filtering for Ultrafast Doppler Imaging using similarity of spatial singular vectors,” IEEE Trans. Med. Imaging, No. 37, 1574-1586 (2018).Google Scholar
- 31.Osipov, L. V., Kulberg, N. S., Leonov, D. V., and Morozov, S. P., “3D Ultrasound: Current State, Emerging Trends and Technologies,” Biomed. Eng., No. 3, 199-203 (2018).Google Scholar