Ultrasonic mapping of the microvasculature: signal alignment.
The ultimate goal of this work was the development of a system capable of estimating the low flow velocities in the microvasculature. Estimation of low velocity flow 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 physiological tissue motion is a critical part of the process of small-vessel flow mapping, and our methods for this alignment are considered in this paper. Each method involves the correlation of pulses acquired from the same line-of-sight. The first method involves the correlation of adjacent pulses (nearest-neighbor), the second involves a single reference line and the third involves averaging the correlation over a set of reference lines. We find that a nearest-neighbor strategy is suboptimal, and that strategies involving a global reference line are superior. A bound on the variance of estimates of the location of the correlation peak is presented. This bound allows us to consider our results in comparison with an absolute limit. Finally, a new algorithm allowing for alignment between lines-of-sight is described, and initial results are presented. Such an algorithm does, in fact, reduce jitter, correct for tissue motion and enables us to better visualize vessel continuity. We find that vessels as small as 40 microm can be mapped in two dimensions using a 50-MHz transducer.
Zagar
B G
BG
Department of Electrical Engineering, Technical University Graz, Austria.
Fornaris
R J
RJ
Ferrara
K W
KW
D000818:Animals; D001783:Blood Flow Velocity; D005123:Eye / Q000098:blood supply; D006801:Humans; D007091:Image Processing, Computer-Assisted; D051379:Mice; D008833:Microcirculation / Q000000981:diagnostic imaging*; D009374:Neoplasms, Experimental / Q000098:blood supply; D019047:Phantoms, Imaging; D011817:Rabbits; D012815:Signal Processing, Computer-Assisted; D014463:Ultrasonography