Abstract
Super-resolution ultrasound (SRUS) can image microvascular structure and flow at subwave-diffraction resolution based on localizing and tracking microbubbles (MBs). Currently, tracking MBs accurately under limited imaging frame rates and high MB concentrations remains a challenge, especially under the effect of cardiac pulsatility and in highly curved vessels. In this study, an acceleration-incorporated MB motion model is introduced into a Kalman tracking framework. The tracking performance was evaluated using simulated microvasculature with different MB motion parameters, concentrations, and acquisition frame rates, and in vivo human breast tumor US datasets. The simulation results show that the acceleration-based method outperformed the nonacceleration-based method at different levels of acceleration and acquisition frame rates and achieved significant improvement in true positive rate (TPR; up to 11.3%) and false negative rate (FNR; up to 13.2%). The proposed method can also reduce errors in vasculature reconstruction via the acceleration-based nonlinear interpolation, compared with linear interpolation (up to [Formula: see text]). The tracking results from temporally downsampled low frame rate in vivo datasets from human breast tumors show that the proposed method has better MB tracking performance than the baseline method, if using results from the initial high frame data as a reference. Finally, the acceleration estimated from tracking results also provides a spatial speed gradient map that may contain extra valuable diagnostic information.