Identification of vascular lumen by singular value decomposition filtering on blood flow velocity distribution.

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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 1302Hz. 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 34dB and 26dB, 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 -28dB 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.