  Purpose: The motion of the common carotid artery tissue layers along the
vessel axis during the cardiac cycle, observed in ultrasound imaging, is
associated with the presence of established cardiovascular risk factors.
However, the vast majority of the methods are based on the tracking of a single
point, thus failing to capture the overall motion of the entire arterial wall.
The aim of this work is to introduce a motion tracking framework able to
simultaneously extract the trajectory of a large collection of points spanning
the entire exploitable width of the image.
  Method: The longitudinal motion, which is the main focus of the present work,
is determined in two steps. First, a series of independent block matching
operations are carried out for all the tracked points. Then, an original
dynamic-programming approach is exploited to regularize the collection of
similarity maps and estimate the globally optimal motion over the entire vessel
wall. Sixty-two atherosclerotic participants at high cardiovascular risk were
involved in this study.
  Results: A dense displacement field, describing the longitudinal motion of
the carotid far wall over time, was extracted. For each cine-loop, the method
was evaluated against manual reference tracings performed on three local
points, with an average absolute error of 150+/-163 um. A strong correlation
was found between motion inhomogeneity and the presence of coronary artery
disease (beta-coefficient=0.586, p=0.003).
  Conclusions: To the best of our knowledge, this is the first time that a
method is specifically proposed to assess the dense motion field of the carotid
far wall. This approach has potential to evaluate the (in)homogeneity of the
wall dynamics. The proposed method has promising performances to improve the
analysis of arterial longitudinal motion and the understanding of the
underlying patho-physiological parameters.
