|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
A DATA WEIGHTING SCHEME FOR QUASISTATIC ULTRASOUND ELASTICITY IMAGING
L.Chen, R.J. Housden, G.M. Treece, A.H. Gee and R.W. Prager
The quality of quasistatic ultrasound strain images depends strongly on post-processing procedures (normalization, spatial and temporal filtering). Such procedures generally benefit from weighting the data to give more credence to high quality strain estimates. In this paper, we evaluate several different quality metrics on each post-processing procedure. The results suggest that no single weighting scheme works best for all procedures. Rather, SNRe is well suited to normalization and a combined variance-based metric to temporal filtering. For spatial filtering, the various quality metrics produce similar results.
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