TY - JOUR
T1 - Simultaneous Noise Suppression and Incoherent Artifact Reduction in Ultrafast Ultrasound Vascular Imaging
AU - Huang, Chengwu
AU - Song, Pengfei
AU - Trzasko, Joshua D.
AU - Gong, Ping
AU - Lok, U. Wai
AU - Tang, Shanshan
AU - Manduca, Armando
AU - Chen, Shigao
N1 - Funding Information:
Manuscript received September 23, 2020; accepted January 26, 2021. Date of publication January 29, 2021; date of current version May 25, 2021. This work was supported in part by the National Cancer Institute of the National Institutes of Health under Award R00CA214523 and in part by the National Institute of Diabetes and Digestive and Kidney Diseases under Award R01DK120559. (Corresponding author: Shigao Chen.) Chengwu Huang, Joshua D. Trzasko, Ping Gong, U-Wai Lok, Shanshan Tang, and Shigao Chen are with the Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, MN 55905 USA (e-mail: chen.shigao. . ayo.edu).
Publisher Copyright:
© 1986-2012 IEEE.
PY - 2021/6
Y1 - 2021/6
N2 - 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.
AB - 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.
KW - Blood
KW - Blood flow
KW - Clutter
KW - Correlation
KW - Imaging
KW - Signal to noise ratio
KW - Ultrasonic imaging
KW - Ultrasound small vessel imaging
KW - artifact suppression
KW - noise suppression
KW - singular value decomposition (SVD)
KW - ultrafast ultrasound
KW - Artifact suppression
KW - ultrasound small vessel imaging
UR - http://www.scopus.com/inward/record.url?scp=85100517411&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100517411&partnerID=8YFLogxK
U2 - 10.1109/TUFFC.2021.3055498
DO - 10.1109/TUFFC.2021.3055498
M3 - Article
C2 - 33513103
AN - SCOPUS:85100517411
SN - 0885-3010
VL - 68
SP - 2075
EP - 2085
JO - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
JF - IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
IS - 6
M1 - 9340246
ER -