3D Image Interpolation Based on Anisotropic Diffusion of Feature Point Correspondence

摘要

An automatic method has been developed to interpolate between neighboring slices in a gray-scale data set by anisotropic diffusion of feature point correspondence. The feature point extracted is registered to form the feature vector. Thus a three dimensional (3D) weight anisotropic vector diffusion is introduced to spread the feature vector to the correspondence vector, which estimates spatial correspondence between adjacent slices. Bilinear interpolation is made along the direction of correspondence vector. Experiments are performed on medical data sets to evaluate the proposed method, showing that the new algorithm achieves good quality and improvement in efficiency relative to the traditional methods.