Fast 3D reconstruction of Ultrasonic Images Based on Generalized Regression Neural Network

In robot-assisted surgery projects researchers should be able to make fast 3D reconstruction. Usually 2D images acquired with common diagnostic equipments such as UT, CT and MRI are not enough and complete for an accurate 3D reconstruction. There are some interpolation methods for approximating non value voxels which consume large execution time. we introduce a novel algorithm based on generalized regression neural network (GRNN) which can interpolate unknown voxles fast and reliable. It is shown that composition of GRNN with image distance transformation can produce higher quality 3D shapes. The results of this method are compared with other interpolation methods practically.

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