|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
UNIFORM PRECISION ULTRASOUND STRAIN IMAGING.
G.M. Treece, J.E. Lindop, A.H. Gee and R.W. Prager
9th March 2009
Ultrasound strain imaging is becoming increasingly popular as a way to measure stiffness variation in soft tissue. Almost all techniques involve the estimation of a field of relative displacements between measurements of tissue undergoing different deformations. These estimates are often high resolution, but some form of smoothing is required to increase the precision, either by direct filtering or as part of the gradient estimation process. Such methods generate uniform resolution images, but strain quality typically varies considerably within each image, hence a trade-off is necessary between increasing precision in the low quality regions and reducing resolution in the high quality regions. We introduce a smoothing technique, developed from the nonparametric regression literature, which can avoid this trade-off by generating uniform precision images. In such an image, high resolution is retained in areas of high strain quality but sacrificed for the sake of increased precision in low quality areas. We contrast the algorithm with other methods on simulated, phantom and clinical data, for both 2D and 3D strain imaging. We also show how the technique can be e±ciently implemented at real time rates with realistic parameters on modest hardware. Uniform precision nonparametric regression promises to be a useful tool in ultrasound strain imaging.
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