Nagaoka Ryo, Hasegawa Hideyuki
Graduate School of Science and Engineering for Research, University of Toyama, 3190 Gofuku, Toyama, 930-8555, Japan.
J Med Ultrason (2001). 2019 Apr;46(2):187-194. doi: 10.1007/s10396-019-00928-4. Epub 2019 Jan 24.
In the present study, we proposed a novel method for identification of the vascular lumen by employing singular value decomposition (SVD), and the feasibility of the proposed method was validated by in vivo measurement of the common carotid artery.
SVD filtering was applied to a velocity map that was estimated using an autocorrelation method to identify the lumen region. In this study, the packet size was set at 999 frames with a frame rate of 1302 Hz. The region estimated by the proposed SVD filtering was compared with that estimated by the conventional power Doppler method.
The averaged differences in feature values between vascular wall and lumen regions obtained by the proposed and conventional methods were 34 dB and 26 dB, respectively. The proposed method was hardly influenced by the cardiac phase and could separate the wall and lumen regions more stably. The proposed method could identify the lumen region by setting a threshold of - 28 dB from the averaged difference amplitude.
We proposed a novel method for identification of the vascular lumen. The proposed method could suppress the effects of wall motion, which was present in the conventional power Doppler image. The lumen region identified by the proposed method well conformed with the anatomical information in the B-mode image of the corresponding section.
在本研究中，我们提出了一种采用奇异值分解（SVD）识别血管腔的新方法，并通过对颈总动脉的体内测量验证了该方法的可行性。
将SVD滤波应用于使用自相关方法估计的速度图，以识别管腔区域。在本研究中，数据包大小设置为999帧，帧率为1302Hz。将所提出的SVD滤波估计的区域与传统功率多普勒方法估计的区域进行比较。
所提出的方法和传统方法获得的血管壁和管腔区域之间特征值的平均差异分别为34dB和26dB。所提出的方法几乎不受心动周期的影响，并且能够更稳定地分离壁和管腔区域。所提出的方法可以通过从平均差异幅度设置-28dB的阈值来识别管腔区域。
我们提出了一种识别血管腔的新方法。所提出的方法可以抑制传统功率多普勒图像中存在的壁运动的影响。所提出的方法识别的管腔区域与相应切片的B模式图像中的解剖信息非常吻合。
