Directed graph based image registration
Directed graph based image registration
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DOI：
10.1016/j.compmedimag.2011.09.001
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发表时间：
2012-03-01
影响因子：
5.7
通讯作者：
Shen, Dinggang
中科院分区：
文献类型：
--
作者：
Jia, Hongjun;Wu, Guorong;Shen, Dinggang
本文提出了一种新颖的图像配准方法，借助一组适当的中间模板来实现形状差异较大的图像之间的精确配准。我们首先证明方向性是成对图像配准和分组配准的关键因素，本文定义方向性是为了描述配准方向和路径对配准性能的影响。在我们的解决方案中，中间模板选择和中间模板引导注册是两个连贯的步骤，并且考虑了方向性。为了利用方向性，基于图像群体中所有有序图像对上定义的非对称距离构建有向图，这与之前所有方法中具有对称距离度量的无向图有本质区别，并计算有向图上模板与主题之间的最短距离。因此，所分配的有向路径可以用于通过在通往模板的路径上通过中间模板一一连续地注册对象来更好地引导注册。所提出的基于有向图的解决方案也可以用于分组配准。具体来说，通过在有向图上构建最小跨度树状结构（MSA），同时确定人口中心（即选定的模板）以及从所有其余图像到人口中心的有向配准路径。基于有向图的配准算法的性能通过合成数据集和真实大脑 MR 图像的空间归一化得到证明。结果表明，我们的方法比基于无向图的解决方案和直接成对配准可以获得更准确的配准结果。 (C) 2011 Elsevier Ltd. 保留所有权利。
In this paper, a novel image registration method is proposed to achieve accurate registration between images having large shape differences with the help of a set of appropriate intermediate templates. We first demonstrate that directionality is a key factor in both pairwise image registration and groupwise registration, which is defined in this paper to describe the influence of the registration direction and paths on the registration performance. In our solution, the intermediate template selection and intermediate template guided registration are two coherent steps with directionality being considered. To take advantage of the directionality, a directed graph is built based on the asymmetric distance defined on all ordered image pairs in the image population, which is fundamentally different from the undirected graph with symmetric distance metrics in all previous methods, and the shortest distance between template and subject on the directed graph is calculated. The allocated directed path can be thus utilized to better guide the registration by successively registering the subject through the intermediate templates one by one on the path towards the template. The proposed directed graph based solution can also be used in groupwise registration. Specifically, by building a minimum spanning arborescence (MSA) on the directed graph, the population center, i.e., a selected template, as well as the directed registration paths from all the rest of images to the population center, is determined simultaneously. The performance of directed graph based registration algorithm is demonstrated by the spatial normalization on both synthetic dataset and real brain MR images. It is shown that our method can achieve more accurate registration results than both the undirected graph based solution and the direct pairwise registration. (C) 2011 Elsevier Ltd. All rights reserved.