Directly Manipulated Free-Form Deformation Image Registration
Directly Manipulated Free-Form Deformation Image Registration
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DOI：
10.1109/tip.2008.2010072
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发表时间：
2009-03-01
影响因子：
10.6
通讯作者：
Gee, James C.
中科院分区：
文献类型：
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作者：
Tustison, Nicholas J.;Avants, Brian B.;Gee, James C.
先前对研究[1]和开放源码软件[2]社区的贡献详细描述了基于Lee等人最初提出的工作的三次B-Spline的快速标量场拟合技术的推广。[3]。我们提出的广义B-Spline拟合方法的一个优点是它直接应用于医学图像分析中经常使用的一类非刚性配准技术。具体地说，这些配准技术属于自由形式变形(FFD)方法的范畴，在FFD方法中，要配准的对象嵌入到B样条线对象中。B样条线对象的变形描述了图像配准解决方案的变换。Rueckert et at的表述是这类技术的代表，并且经常在相关社区中被引用。[4]他们使用具有归一化互信息的三次样条法来研究乳房变形。来自不同组的类似技术以不同的显式正则化术语的形式提供了增量新颖性，以及各种图像度量和量身定制的优化方法的使用。对于几种算法，基本的基于梯度的优化保留了Rueckert原始贡献的本质特征。我们在本文中提供的贡献有两个方面：1)观察到通用的FFD框架本质上对有问题的能量地形敏感；2)FFD图像配准中使用的标准梯度可以修改为易于理解的预条件形式，从而显著提高性能。理论探讨和对比评价实验证明了这一点。
Previous contributions to both the research [1] and open source software [2] communities detailed a generalization of a fast scalar field fitting technique for cubic B-splines based on the work originally proposed by Lee et al. [3]. One advantage of our proposed generalized B-spline fitting approach is its immediate application to a class of nonrigid registration techniques frequently employed in medical image analysis. Specifically, these registration techniques fall under the rubric of free-form deformation (FFD) approaches in which the object to be registered is embedded within a B-spline object. The deformation of the B-spline object describes the transformation of the image registration solution. Representative of this class of techniques, and often cited within the relevant community, is the formulation of Rueckert et at. [4] who employed cubic splines with normalized mutual information to study breast deformation. Similar techniques from various groups provided incremental novelty in the form of disparate explicit regularization terms, as well as the employment of various image metrics and tailored optimization methods. For several algorithms, the underlying gradient-based optimization retained the essential characteristics of Rueckert's original contribution. The contribution which we provide in this paper is two-fold: 1) the observation that the generic FFD framework is intrinsically susceptible to problematic energy topographies and 2) that the standard gradient used in FFD image registration can be modified to a well-understood preconditioned form which substantially improves performance. This is demonstrated with theoretical discussion and comparative evaluation experimentation.