学术文献库

Vascular networks can provide invaluable information about tumor angiogenesis. Ultrafast Doppler imaging enables ultrasound to image micro-vessels by applying tissue clutter filtering methods on the Spatio-temporal data obtained from plane-wave imaging. However, motion is an intrinsic part of microvasculature imaging due to various reasons e.g breathing and vessel pulsation. Part of such a motion is taken care of by using Spatio-temporal cluttering filtering. Nonetheless, the remaining part of the motion who manifests itself as blurring or generating ghost vessels should be corrected using another level of motion compensation. We proposed a robust and computationally efficient motion compensation algorithm for Ultrasound micro-vessel imaging. We successfully evaluated the performance of the algorithm by a simulation study. Finally, we tested the proposed motion compensation method on the in vivo data of microvasculature in different organs including breast and thyroid. Results show blurring and ghost vessel problems are significantly reduced using the proposed algorithm. Moreover, our quantitative assessment demonstrated that image correlation among different frames in Ultrafast Doppler imaging is significantly improved utilizing the proposed motion correction method.