Joint registration and segmentation of neuroanatomic structures from brain MRI
Joint registration and segmentation of neuroanatomic structures from brain MRI
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DOI：
10.1016/j.acra.2006.05.017
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发表时间：
2006-09-01
影响因子：
4.8
通讯作者：
Eisenschenk, Stephan J.
中科院分区：
文献类型：
--
作者：
Wang, Fei;Vemuri, Baba C.;Eisenschenk, Stephan J.
理由和目标。从磁共振脑扫描分割解剖结构可能是一项艰巨的任务，因为跨图像的图像强度存在很大的不均匀性，并且可能缺乏针对某些解剖结构的精确定义的形状边界。在最近的过去，对于这些情况，一种非常流行的方法是基于地图集的分割。图谱一旦构建，就可以用作模板，并且可以非刚性地配准到被分割的图像，从而实现期望的分割。我们研究的目标是用配准辅助图像分割技术分割这些结构。我们提出了一种新的配准辅助图像分割问题的变分制剂，导致解决一组耦合的非线性偏微分方程（PDE），使用高效的数值方案解决。我们的工作是从早期的方法，我们可以同时登记和分割在三维和容易地科普的情况下，源（图集）和目标图像具有非常明显的强度分布。我们提出了几个例子（20）合成和（3）真实的数据集沿着与定量精度估计的注册在合成数据的情况下。所提出的基于图集的分割技术是能够同时实现非刚性配准和分割，与以前的方法解决这个问题，我们的算法可以适应具有非常不同的强度分布的图像对。
Rationale and Objectives. Segmentation of anatomic structures from magnetic resonance brain scans can be a daunting task because of large inhomogeneities in image intensities across an image and possible lack of precisely defined shape boundaries for certain anatomical structures. One approach that has been quite popular in the recent past for these situations is the atlas-based segmentation. The atlas, once constructed, can be used as a template and can be registered nonrigidly to the image being segmented thereby achieving the desired segmentation. The goal of our study is to segment these structures with a registration assisted image segmentation technique.Materials and Methods. We present a novel variational formulation of the registration assisted image segmentation problem which leads to solving a coupled set of nonlinear Partial Differential Equations (PDEs) that are solved using efficient numeric schemes. Our work is a departure from earlier methods in that we can simultaneously register and segment in three dimensions and easily cope with situations where the source (atlas) and target images have very distinct intensity distributions.Results. We present several examples (20) on synthetic and (3) real data sets along with quantitative accuracy estimates of the registration in the synthetic data case.Conclusion. The proposed atlas-based segmentation technique is capable of simultaneously achieve the nonrigid registration and the segmentation; unlike previous methods of solution for this problem, our algorithm can accommodate for image pairs having very distinct intensity distributions.