将ICP算法扩展到基于非刚性强度的三维体配准

J. Feldmar, G. Malandain, J. Declerck, N. Ayache
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引用次数: 52

摘要

提出了一种新的三维医学图像配准与增益校正算法。这是基于强度的。基本思想是用4D点(x/sub j/, y/sub j/, z/sub j/, i/sub j/)表示图像,并根据这种表示定义一个全局能量函数。为了最小化,作者提出了一种不需要计算该准则相对于参数的导数的技术。它可以理解为迭代最近点算法的扩展(P. Besl和N. McKay, 1992;Z. Zhang, 1992)或作为L. Cohen提出的形式主义的应用(计算机视觉问题中辅助变量的使用)。第五届计算机视觉国际会议论文集(ICCV '95),波士顿,1995年6月)。两个参数允许一个有一个粗到细的策略,无论是分辨率和变形。作者的技术的优势在于最小化一个定义良好的全局准则来处理各种类型的变换(例如刚性、仿射和体积样条),实现简单,在实践中效率高。在真实的大脑和心脏三维图像上的结果证明了作者方法的有效性。
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Extension of the ICP algorithm to non-rigid intensity-based registration of 3D volumes
Presents a new registration and gain correction algorithm for 3D medical images. It is intensity based. The basic idea is to represent the images by 4D points (x/sub j/, y/sub j/, z/sub j/, i/sub j/) and to define a global energy function based on this representation. For minimization, the authors propose a technique which does not require to compute the derivatives of this criterion with respect to the parameters. It can be understood as an extension of the Iterative Closest Point algorithm (P. Besl and N. McKay, 1992; Z. Zhang, 1992) or as an application of the formalism proposed by L. Cohen (Use of auxiliary variables in computer vision problems. In Proceedings of the Fifth International Conference on Computer Vision (ICCV '95), Boston, June 1995). Two parameters allow one to have a coarse to fine strategy both for resolution and deformation. The authors' technique presents the advantage to minimize a well defined global criterion to deal with various classes of transformations (for example rigid, affine and volume spline), to be simple to implement and to be efficient in practice. Results on real brain and heart 3D images are presented to demonstrate the validity of the authors' approach.
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