|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
RADIAL BASIS FUNCTION INTERPOLATION FOR 3-D ULTRASOUND
Rohling, R., Gee, A. and Berman, L.
3-D freehand ultrasound imaging produces a set of irregularly spaced B-scans, which are typically reconstructed on a regular grid for visualisation and data analysis. Most standard reconstruction algorithms are designed to minimise computational requirements and do not exploit the underlying shape of the data. We investigate whether approximation with splines holds any promise as a better reconstruction method. A radial basis function (RBF) approximation method is implemented and compared with three standard methods. The RBF's are shown to accommodate both dense, overlapping data and sparse data, without introducing the kind of reconstruction artifacts common with the standard methods. The other potential advantages of RBF's, such as the direct computation of derivatives, make further investigation worthwhile.
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