Non-rigid registration by geometry-constrained diffusion
Non-rigid registration by geometry-constrained diffusion
复制标题
DOI：
10.1016/s1361-8415(00)00036-0
复制
发表时间：
2001-06-01
影响因子：
10.9
通讯作者：
Nielsen, M
中科院分区：
文献类型：
--
作者：
Andresen, PR;Nielsen, M
假设仅给出关于非刚性配准的部分知识：已知一个3D图像中的某些点、曲线或表面映射到另一3D图像中的某些点、曲线或表面。在试图确定非刚性位移场，我们面临着一个广义孔径问题，因为沿着的曲线和曲面，点对应是不给。我们主张通过寻找最简单的位移场，可以同时解决孔径和三维插值问题。这是通过几何约束的扩散，在精确的意义上产生最简单的位移场。所获得的点配准可以用于分割、生长建模、形状分析或运动插值。该算法适用于任何维度的几何对象。因此，我们可以保持任何数量的基准点、曲线和/或表面固定，同时找到最简单的配准。在一个合成的例子和人类下颌骨的纵向生长研究推断点对应的例子。(C)2001 Elsevier Science B. V.保留所有权利。
Assume that only partial knowledge about a non-rigid registration is given: certain points, curves or surfaces in one 3D image are known to map to certain points, curves or surfaces in another 3D image. In trying to identify the non-rigid displacement field, we face a generalized aperture problem since along the curves and surfaces, point correspondences are not given. We will advocate the viewpoint that the aperture and the 3D interpolation problem may be solved simultaneously by finding the simplest displacement field. This is obtained by a geometry-constrained diffusion, which in a precise sense yields the simplest displacement field. The point registration obtained may be used for segmentation, growth modeling, shape analysis or kinematic interpolation. The algorithm applies to geometrical objects of any dimensionality. We may thus keep any number of fiducial points, curves and/or surfaces fixed while finding the simplest registration. Examples of inferred point correspondences in a synthetic example and a longitudinal growth study of the human mandible are given. (C) 2001 Elsevier Science B.V. All rights reserved.