The ultimate goal of this work was the development of a system capable
of estimating the low how velocities in the microvasculature, Estimat
ion of low velocity how within these vessels is challenging due to the
small signal levels and the effect of cardiac and respiratory motion.
Realignment of the signal from a single line-of-sight to remove physi
ological tissue motion is a critical part of the process of small-vess
el flow mapping, and our methods for this alignment are considered in
this paper. Each method involves the correlation of pulses acquired fr
om the same line-of-sight. The first method involves the correlation o
f adjacent pulses (nearest-neighbor), the second involves a single ref
erence line and the third involves averaging the correlation over a se
t of reference lines. We find that a nearest-neighbor strategy is subo
ptimal, and that strategies involving a global reference line are supe
rior. A bound on the variance of estimates of the location of the corr
elation peak is presented. This bound allows us to consider our result
s in comparison with an absolute limit. Finally, a new algorithm allow
ing for alignment between lines-of-sight is described, and initial res
ults are presented. Such an algorithm does, in fact, reduce jitter, co
rrect for tissue motion and enables us to better visualize vessel cont
inuity. We find that vessels as small as 40 mu m can be mapped in two
dimensions using a 50-MHz transducer. (C) 1998 World Federation for Ul
trasound in Medicine & Biology.