# Iterative 2D Tissue Motion Tracking in Ultrafast Ultrasound Imaging
## 4 Discussion
However, the ultrasound scanner that was used on the phantom set-up is a research scanner without, e.g., virtual scan lines, whereas the scanner we used to perform state-of-the-art tracking in vivo is a commercial ultrasound scanner utilizing virtual scan lines and many other techniques that improve the image quality. Several studies have shown that the tracking performance is sufficient when using low frame rate imaging with a conventional linear scan scheme [26; 28; 32; 33; 34; 35; 36]. The frame rate in these studies varies between 30-100 Hz. The benefit of the implemented iterative method came not only from the use of two kernels for each estimation but also from the length of the movement between the frames in the first iteration. Considering that the initial length of iteration should be \"long enough\" for the best tracking accuracy and that the velocities vary drastically in in vivo measurements, it is likely that the tracking performance of the proposed tracking scheme can be optimized in vivo by using an initial length of iteration that adapts to the tissue velocity aiming to achieve the longest possible movement without significant speckle decorrelation. Potentially the best results could be achieved by using two estimations of the movement in a cine loop: the first one determining the overall shape of the movement using a fixed frame rate, e.g., 50 Hz corresponding to \(k\) = 32, in order to maximize the initial length of iteration for each part of the cine loop; the second estimation determining the movement in all frames. Tracking of the longitudinal movement of the arterial wall frame-to-frame using the combination block-matching and ultrafast ultrasound imaging does not work. Though no ground-truth exists, the major movement patterns in vivo using our proposed iterative tracking scheme correspond well with low frame rate motion estimates, indicating that the proposed tracking scheme could enable the study of longitudinal movement imaging of the intima-media complex using ultrafast ultrasound imaging. However, caution should be taken when drawing conclusions from these results as the magnitudes of the estimation errors on the in vivo measurements are yet unknown. In the subjects investigated, we obtained the best result using two different initial lengths of iteration (\(k\) = 32 and 64). Further studies are needed to individually optimize the \(k\). The tracking scheme presented here is easy to implement and we believe that it can be used with most motion estimation methods with a Lagrangian viewpoint. In our implementation, the computational load is the same for any \(k\). There are two limitations in the phantom study. The first limitation is the chosen constant velocities of the phantom. With a maximal velocity of 2 mm/s, we are well below fast tissue motions in vivo. The second limitation is that the largest initial length of iterations was \(k\) = 128. Larger values of \(k\) were not possible to test due to the combination of using a Lagrangian viewpoint, the velocity of the phantom, and the size of the ultrasound frames. However, we do not know whether a continued increase of \(k\) will be beneficial as speckle decorrelation and out-of-plane movement can be increasingly problematic. Also, the results from the in vivo measurement (Figures 8 and 9), where \(k\) = 32 and 64, were optimal, indicating that the proposed tracking scheme does not necessarily continue to improve with increased \(k\) when used on in vivo measurements. Further studies, preferably with simulated data or a larger set of in vivo cine loops, are needed. Undesirable fluctuations, which are considered to be caused by pitching and yawing of the automatic stages and electrical noise in the measurement system, were contained in the estimated lateral and axial velocities. However, displacements due to such cyclic components, which are presumably caused by pitching and yawing of the automatic stages, were very small.