Abstract

In three-dimensional (3D) freehand ultrasound (US), reconstructing a set of B-scans into a regular voxel array is the key procedure for consequent visualization and analysis. This paper presents a new adaptive interpolation algorithm for computing the voxel array to suppress speckle noises and enhance contrast. The local statistics of homogeneous regions including mean and variance were measured and the ratio of variance to mean was used as homogeneity criteria. For the computation of each voxel, the interpolation method was adaptively determined with respect to its local statistics. If the neighbouring pixels of a voxel satisfied the homogeneity criterion, its value was computed with an arithmetic mean filter. Otherwise, the voxel was probably locating in an inhomogeneous region and an adaptive distance-weighted (ADW) interpolation method was employed to compute its value. A resolution phantom and a subject’s forearm were reconstructed using the proposed algorithm and two other well-known methods – conventional distance-weighted (DW) and voxel nearest neighbourhood (VNN) interpolations. The comparison results demonstrated that the adaptive interpolation algorithm was able to suppress speckles, preserve edges and enhance contrast effectively for the volume reconstruction.

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