Journal
IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL
Volume 68, Issue 6, Pages 2075-2085Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TUFFC.2021.3055498
Keywords
Imaging; Ultrasonic imaging; Clutter; Blood; Correlation; Blood flow; Signal to noise ratio; Artifact suppression; noise suppression; singular value decomposition (SVD); ultrafast ultrasound; ultrasound small vessel imaging
Categories
Funding
- National Cancer Institute of the National Institutes of Health [R00CA214523]
- National Institute of Diabetes and Digestive and Kidney Diseases [R01DK120559]
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A method combining coherent spatial compounding, SVD clutter filtering, and correlation processing is proposed to suppress background noise and incoherent artifacts in ultrasound vascular imaging, resulting in improved blood flow visualization. Evaluation in wire-target simulations and phantom showed SNR improvement, and consistent results were found in flow channel phantom testing against conventional power Doppler. The method was further demonstrated in human liver, breast tumor, and inflammatory bowel disease data sets, showing potential for more reliable small vessel imaging for various clinical applications.
Ultrasound vascular imaging based on ultrafast plane wave imaging and singular value decomposition (SVD) clutter filtering has demonstrated superior sensitivity in blood flow detection. However, ultrafast ultrasound vascular imaging is susceptible to electronic noise due to the weak penetration of unfocused waves, leading to a lower signal-to-noise ratio (SNR) at larger depths. In addition, incoherent clutter artifacts originating from strong and moving tissue scatterers that cannot be completely removed create a strong mask on top of the blood signal that obscures the vessels. Herein, a method that can simultaneously suppress the background noise and incoherent artifacts is proposed. The method divides the tilted plane or diverging waves into two subgroups. Coherent spatial compounding is performed within each subgroup, resulting in two compounded data sets. An SVD-based clutter filter is applied to each data set, followed by a correlation between the two data sets to produce a vascular image. Uncorrelated noise and incoherent artifacts can be effectively suppressed with the correlation process, while the coherent blood signal can be preserved. The method was evaluated in wire-target simulations and phantom, in which around 7-10-dB SNR improvement was shown. Consistent results were found in a flow channel phantom with improved SNR by the proposed method (39.9 +/- 0.2 dB) against conventional power Doppler (29.1 +/- 0.6 dB). Last, we demonstrated the effectiveness of the method combined with block-wise SVD clutter filtering in a human liver, breast tumor, and inflammatory bowel disease data sets. The improved blood flow visualization may facilitate more reliable small vessel imaging for a wide range of clinical applications, such as cancer and inflammatory diseases.
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