Matching 3-D anatomical surfaces with non-rigid deformations using octree-splines

作者:Richard Szeliski, Stéphane Lavallée

摘要

This paper presents a new method for determining the minimal non-rigid deformation between two 3-D surfaces, such as those which describe anatomical structures in 3-D medical images. Although we match surfaces, we represent the deformation as a volumetric transformation. Our method performs a least squares minimization of the distance between the two surfaces of interest. To quickly and accurately compute distances between points on the two surfaces, we use a precomputed distance map represented using an octree spline whose resolution increases near the surface. To quickly and robustly compute the deformation, we use a second octree spline to model the deformation function. The coarsest level of the deformation encodes the global (e.g., affine) transformation between the two surfaces, while finer levels encode smooth local displacements which bring the two surfaces into closer registration. We present experimental results on both synthetic and real 3-D surfaces.

论文关键词:Image Processing, Artificial Intelligence, Computer Vision, Medical Image, Computer Image

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论文官网地址:https://doi.org/10.1007/BF00055001