Automatic Classification of Arterial and Venous Flow in Super-resolution Ultrasound Images of Rat Kidneys
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Standard
Automatic Classification of Arterial and Venous Flow in Super-resolution Ultrasound Images of Rat Kidneys. / Taghavi, Iman; Andersen, Sofie Bech; Sogaard, Stinne Byrholdt; Nielsen, Michael Bachmann; Sorensen, Charlotte Mehlin; Stuart, Matthias Bo; Jensen, Jorgen Arendt.
2021 IEEE International Ultrasonics Symposium (IUS). IEEE, 2021. (IEEE International Ultrasonics Symposium, IUS).Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review
Harvard
APA
Vancouver
Author
Bibtex
}
RIS
TY - GEN
T1 - Automatic Classification of Arterial and Venous Flow in Super-resolution Ultrasound Images of Rat Kidneys
AU - Taghavi, Iman
AU - Andersen, Sofie Bech
AU - Sogaard, Stinne Byrholdt
AU - Nielsen, Michael Bachmann
AU - Sorensen, Charlotte Mehlin
AU - Stuart, Matthias Bo
AU - Jensen, Jorgen Arendt
N1 - Publisher Copyright: © 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Velocity is one of the clinically interesting parameters. A number of studies have shown the ability of super-resolution (SR) ultrasound imaging to visualize this parameter using velocity maps. However, manual separation of the velocity estimates for arteries from veins can be quite demanding. This study used the anatomical knowledge of rat kidneys for automatic classification of arterial and venous blood velocities in SR images and measured their variations in the medullary regions of four healthy Sprague-Dawley rat kidneys. The measurements were conducted using a modified bk5000 scanner (BK Medical, Herlev, Denmark) and a BK 9009 linear array probe with a pulse amplitude modulation scheme. Ten minutes of acquired B-mode and contrast images with frame-rate of 54 Hz were processed using a SR processing pipeline. The micro-bubble trajectories were filtered using coarse anatomy labels for classification of arterial and venous flow. The velocity estimates of separated arterioles and venules of the outer medulla showed separation of data in all rats. A Wilcoxon test showed that this difference was statistically significant (p=0.002). Considering the sample size for this study, the t-distributions predicted that the median velocity in the OM arterioles and venules were in the range of 0.84 ± 0.09 mm/s and 0.70 ± 0.07 mm/s with 95% confidence. The result showed how the blood flow in outer medulla arterioles and venules of rat kidneys can be automatically distinguished using the known anatomical information about the renal vasculature.
AB - Velocity is one of the clinically interesting parameters. A number of studies have shown the ability of super-resolution (SR) ultrasound imaging to visualize this parameter using velocity maps. However, manual separation of the velocity estimates for arteries from veins can be quite demanding. This study used the anatomical knowledge of rat kidneys for automatic classification of arterial and venous blood velocities in SR images and measured their variations in the medullary regions of four healthy Sprague-Dawley rat kidneys. The measurements were conducted using a modified bk5000 scanner (BK Medical, Herlev, Denmark) and a BK 9009 linear array probe with a pulse amplitude modulation scheme. Ten minutes of acquired B-mode and contrast images with frame-rate of 54 Hz were processed using a SR processing pipeline. The micro-bubble trajectories were filtered using coarse anatomy labels for classification of arterial and venous flow. The velocity estimates of separated arterioles and venules of the outer medulla showed separation of data in all rats. A Wilcoxon test showed that this difference was statistically significant (p=0.002). Considering the sample size for this study, the t-distributions predicted that the median velocity in the OM arterioles and venules were in the range of 0.84 ± 0.09 mm/s and 0.70 ± 0.07 mm/s with 95% confidence. The result showed how the blood flow in outer medulla arterioles and venules of rat kidneys can be automatically distinguished using the known anatomical information about the renal vasculature.
U2 - 10.1109/IUS52206.2021.9593655
DO - 10.1109/IUS52206.2021.9593655
M3 - Article in proceedings
AN - SCOPUS:85122850066
SN - 978-0-7381-1209-1
T3 - IEEE International Ultrasonics Symposium, IUS
BT - 2021 IEEE International Ultrasonics Symposium (IUS)
PB - IEEE
T2 - 2021 IEEE International Ultrasonics Symposium, IUS 2021
Y2 - 11 September 2011 through 16 September 2011
ER -
ID: 302544176