Towards fast non-rigid registration

Abstract

A fast multiscale and multigrid method for the matching of images in 2D and 3D is presented. Especially in medical imaging this problem - denoted as the registration problem - is of fundamental importance in the handling of images from multiple image modalities or of image time series. The paper restricts to the simplest matching energy to be minimized, i.e., \t are the intensity maps of the two images to be matched and is a deformation. The focus is on a robust and efficient solution strategy. Matching of images, i.e., finding an optimal deformation which minimizes is known to be an ill-posed problem. Hence, to regularize this problem a regularization of the descent path is considered in a gradient flow method. Thus the initial value problem with some regular initial deformation "!#%$ is solved on a suitable space of deformations &(')& . The gradient grad is measured w.r.t a suitable regularizing metric . Existence and uniqueness of solutions is demonstrated for different types of regularizations. For the implementation a metric based on multigrid cycles on hierarchical grids is proposed, using their superior smoothing properties. This is combined with an effective time-step control in the descent algorithm. Furthermore, to avoid convergence to local minima, multiple scales of the images to be matched are considered. Again, these image scales can be generated applying multigrid operators and we propose to resolve the pyramid of scales on a properly chosen pyramid of hierarchical grids. Examples on 2D and large 3D image matching problems prove the robustness and efficiency of the proposed approach.

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